Speech - Text-To-Speech Synthesis in .NET (2023)

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June 2019

Volume 34 Number 6


By Ilia Smirnov | June 2019

I often fly to Finland to see my mom. Every time the plane lands in Vantaa airport, I’m surprised at how few passengers head for the airport exit. The vast majority set off for connecting flights to destinations spanning all of Central and Eastern Europe. It’s no wonder, then, that when the plane begins its descent, there’s a barrage of announcements about connecting flights. “If your destination is Tallinn, look for gate 123,” “For flight XYZ to Saint Petersburg, proceed to gate 234,” and so on. Of course, flight attendants don’t typically speak a dozen languages, so they use English, which is not the native language of most passengers. Considering the quality of the public announcement (PA) systems on the airliners, plus engine noise, crying babies and other disturbances, how can any information be effectively conveyed?

Well, each seat is equipped with headphones. Many, if not all, long-distance planes have individual screens today (and local ones have at least different audio channels). What if a passenger could choose the language for announcements and an onboard computer system allowed flight attendants to create and send dynamic (that is, not pre-recorded) voice messages? The key challenge here is the dynamic nature of the messages. It’s easy to pre-record safety instructions, catering options and so on, because they’re rarely updated. But we need to create messages literally on the fly.

Fortunately, there’s a mature technology that can help: text-to-speech synthesis (TTS). We rarely notice such systems, but they’re ubiquitous: public announcements, prompts in call centers, navigation devices, games, smart devices and other applications are all examples where pre-recorded prompts aren’t sufficient or using a digitized waveform is proscribed due to memory limitations (a text read by a TTS engine is much smaller to store than a digitized waveform).

Computer-based speech synthesis is hardly new. Telecom companies invested in TTS to overcome the limitations of pre-recorded messages, and military researchers have experimented with voice prompts and alerts to simplify complex control interfaces. Portable synthesizers have likewise been developed for people with disabilities. For an idea of what such devices were capable of 25 years ago, listen to the track “Keep Talking” on the 1994 Pink Floyd album “The Division Bell,” where Stephen Hawking says his famous line: “All we need to do is to make sure we keep talking.”

TTS APIs are often provided along with their “opposite”—speech recognition. While you need both for effective human-computer interaction, this exploration is focused specifically on speech synthesis. I’ll use the Microsoft .NET TTS API to build a prototype of an airliner PA system. I’ll also look under the hood to understand the basics of the “unit selection” approach to TTS. And while I’ll be walking through the construction of a desktop application, the principles here apply directly to cloud-based solutions.

Roll Your Own Speech System

Before prototyping the in-flight announcement system, let’s explore the API with a simple program. Start Visual Studio and create a console application. Add a reference to System.Speech and implement the method in Figure 1.

(Video) C#/.NET Simple Text to Speech and Speech Recognition

Figure 1 System.Speech.Synthesis Method

using System.Speech.Synthesis;namespace KeepTalking{ class Program { static void Main(string[] args) { var synthesizer = new SpeechSynthesizer(); synthesizer.SetOutputToDefaultAudioDevice(); synthesizer.Speak("All we need to do is to make sure we keep talking"); } }}

Now compile and run. Just a few lines of code and you’ve replicated the famous Hawking phrase.

When you were typing this code, IntelliSense opened a window with all the public methods and properties of the SpeechSynthesizer class. If you missed it, use “Control-Space” or the “dot” keyboard shortcut (or look at bit.ly/2PCWpat). What’s interesting here?

First, you can set different output targets. It can be an audio file or a stream or even null. Second, you have both synchronous (as in the previous example) and asynchronous output. You can also adjust the volume and the rate of speech, pause and resume it, and receive events. You can also select voices. This feature is important here, because you’ll use it to generate output in different languages. But what voices are available? Let’s find out, using the code in Figure 2.

Figure 2 Voice Info Code

using System;using System.Speech.Synthesis;namespace KeepTalking{ class Program { static void Main(string[] args) { var synthesizer = new SpeechSynthesizer(); foreach (var voice in synthesizer.GetInstalledVoices()) { var info = voice.VoiceInfo; Console.WriteLine($"Id: {info.Id} | Name: {info.Name} | Age: {info.Age} | Gender: {info.Gender} | Culture: {info.Culture}"); } Console.ReadKey(); } }}

On my machine with Windows 10 Home the resulting output from Figure 2 is:

Id: TTS_MS_EN-US_DAVID_11.0 | Name: Microsoft David Desktop | Age: Adult | Gender: Male | Culture: en-USId: TTS_MS_EN-US_ZIRA_11.0 | Name: Microsoft Zira Desktop | Age: Adult | Gender: Female | Culture: en-US

There are only two English voices available, and what about other languages? Well, each voice takes some disk space, so they’re not installed by default. To add them, navigate to Start | Settings | Time & Language | Region & Language and click Add a language, making sure to select Speech in optional features. While Windows supports more than 100 languages, only about 50 support TTS. You can review the list of supported languages at bit.ly/2UNNvba.

After restarting your computer, a new language pack should be available. In my case, after adding Russian, I got a new voice installed:

Id: TTS_MS_RU-RU_IRINA_11.0 | Name: Microsoft Irina Desktop | Age: Adult | Gender: Female | Culture: ru-RU

Now you can return to the first program and add these two lines instead of the synthesizer.Speak call:

synthesizer.SelectVoice("Microsoft Irina Desktop");synthesizer.Speak("Всё, что нам нужно сделать, это продолжать говорить");

If you want to switch between languages, you can insert Select­Voice calls here and there. But a better way is to add some structure to speech. For that, let’s use the PromptBuilder class, as shown in Figure 3.

Figure 3 The PromptBuilder Class

(Video) C# Text To Speech (TTS) Synthesis Coding with Speech.Synthesis API (Easy)

using System.Globalization;using System.Speech.Synthesis;namespace KeepTalking{ class Program { static void Main(string[] args) { var synthesizer = new SpeechSynthesizer(); synthesizer.SetOutputToDefaultAudioDevice(); var builder = new PromptBuilder(); builder.StartVoice(new CultureInfo("en-US")); builder.AppendText("All we need to do is to keep talking."); builder.EndVoice(); builder.StartVoice(new CultureInfo("ru-RU")); builder.AppendText("Всё, что нам нужно сделать, это продолжать говорить"); builder.EndVoice(); synthesizer.Speak(builder); } }}

Notice that you have to call EndVoice, otherwise you’ll get a runtime error. Also, I used CultureInfo as another way to specify a language. PromptBuilder has lots of useful methods, but I want to draw your attention to AppendTextWithHint. Try this code:

var builder = new PromptBuilder();builder.AppendTextWithHint("3rd", SayAs.NumberOrdinal);builder.AppendBreak();builder.AppendTextWithHint("3rd", SayAs.NumberCardinal);synthesizer.Speak(builder);

Another way to structure input and specify how to read it is to use Speech Synthesis Markup Language (SSML), which is a cross-platform recommendation developed by the international Voice Browser Working Group (w3.org/TR/speech-synthesis). Microsoft TTS engines provide comprehensive support for SSML. This is how to use it:

string phrase = @"<speak version=""1.0"" https://www.w3.org/2001/10/synthesis"" xml:lang=""en-US"">";phrase += @"<say-as interpret-as=""ordinal"">3rd</say-as>";phrase += @"<break time=""1s""/>";phrase += @"<say-as interpret-as=""cardinal"">3rd</say-as>";phrase += @"</speak>";synthesizer.SpeakSsml(phrase);

Notice it employs a different call on the SpeechSynthesizer class.

Now you’re ready to work on the prototype. This time create a new Windows Presentation Foundation (WPF) project. Add a form and a couple of buttons for prompts in two different languages. Then add click handlers as shown in the XAML in Figure 4.

Figure 4 The XAML Code

using System.Collections.Generic;using System.Globalization;using System.Speech.Synthesis;using System.Windows;namespace GuiTTS{ public partial class MainWindow : Window { private const string en = "en-US"; private const string ru = "ru-RU"; private readonly IDictionary<string, string> _messagesByCulture = new Dictionary<string, string>(); public MainWindow() { InitializeComponent(); PopulateMessages(); } private void PromptInEnglish(object sender, RoutedEventArgs e) { DoPrompt(en); } private void PromptInRussian(object sender, RoutedEventArgs e) { DoPrompt(ru); } private void DoPrompt(string culture) { var synthesizer = new SpeechSynthesizer(); synthesizer.SetOutputToDefaultAudioDevice(); var builder = new PromptBuilder(); builder.StartVoice(new CultureInfo(culture)); builder.AppendText(_messagesByCulture[culture]); builder.EndVoice(); synthesizer.Speak(builder); } private void PopulateMessages() { _messagesByCulture[en] = "For the connection flight 123 to Saint Petersburg, please, proceed to gate A1"; _messagesByCulture[ru] = "Для пересадки на рейс 123 в Санкт-Петербург, пожалуйста, пройдите к выходу A1"; } }}

Obviously, this is just a tiny prototype. In real life, PopulateMessages will probably read from an external resource. For example, a flight attendant can generate a file with messages in multiple languages by using an application that calls a service like Bing Translator (bing.com/translator). The form will be much more sophisticated and dynamically generated based on available languages. There will be error handling and so on. But the point here is to illustrate the core functionality.

Deconstructing Speech

So far we’ve achieved our objective with a surprisingly small codebase. Let’s take an opportunity to look under the hood and better understand how TTS engines work.

There are many approaches to constructing a TTS system. Historically, researchers have tried to discover a set of pronunciation rules on which to build algorithms. If you’ve ever studied a foreign language, you’re familiar with rules like “Letter ‘c’ before ‘e,’ ‘i,’ ‘y’ is pronounced as ‘s’ as in ‘city,’ but before ‘a,’ ‘o,’ ’u’ as ‘k’ as in ‘cat.’” Alas, there are so many exceptions and special cases—like pronunciation changes in consecutive words—that constructing a comprehensive set of rules is difficult. Moreover, most such systems tend to produce a distinct “machine” voice—imagine a beginner in a foreign language pronouncing a word letter-by-letter.

For more naturally sounding speech, research has shifted toward systems based on large databases of recorded speech fragments, and these engines now dominate the market. Commonly known as concatenation unit selection TTS, these engines select speech samples (units) based on the input text and concatenate them into phrases. Usually, engines use two-stage processing closely resembling compilers: First, parse input into an internal list- or tree-like structure with phonetic transcription and additional metadata, and then synthesize sound based on this structure.

Because we’re dealing with natural languages, parsers are more sophisticated than for programming languages. So beyond tokenization (finding boundaries of sentences and words), parsers must correct typos, identify parts of speech, analyze punctuation, and decode abbreviations, contractions and special symbols. Parser output is typically split by phrases or sentences, and formed into collections describing words that group and carry metadata such as part of speech, pronunciation, stress and so on.

Parsers are responsible for resolving ambiguities in the input. For example, what is “Dr.”? Is it “doctor” as in “Dr. Smith,” or “drive” as in “Privet Drive?” And is “Dr.” a sentence because it starts with an uppercase letter and ends with a period? Is “project” a noun or a verb? This is important to know because the stress is on different syllables.

(Video) C# - Text To Speech using Speech.Synthesis

These questions are not always easy to answer and many TTS systems have separate parsers for specific domains: numerals, dates, abbreviations, acronyms, geographic names, special forms of text like URLs and so on. They’re also language- and region-specific. Luckily, such problems have been studied for a long time and we have well-developed frameworks and libraries to lean on.

The next step is generating pronunciation forms, such as tagging the tree with sound symbols (like transforming “school” to “s k uh l”). This is done by special grapheme-to-phoneme algorithms. For languages like Spanish, some relatively straightforward rules can be applied. But for others, like English, pronunciation differs significantly from the written form. Statistical methods are then employed along with databases for known words. After that, additional post-lexical processing is needed, because the pronunciation of words can change when combined in a sentence.

While parsers try to extract all possible information from the text, there’s something that’s so elusive that it’s not extractable: prosody or intonation. While speaking, we use prosody to emphasize certain words, to convey emotion, and to indicate affirmative sentences, commands and questions. But written text doesn’t have symbols to indicate prosody. Sure, punctuation offers some context: A comma means a slight pause, while a period means a longer one, and a question mark means you raise your intonation toward the end of a sentence. But if you’ve ever read your children a bedtime story, you know how far these rules are from real reading.

Moreover, two different people often read the same text differently (ask your children who is better at reading bedtime stories—you or your spouse). Because of this you cannot reliably use statistical methods since different experts will produce different labels for supervised learning. This problem is complex and, despite intensive research, far from being solved. The best programmers can do is use SSML, which has some tags for prosody.

Neural Networks in TTS

Statistical or machine learning methods have for years been applied in all stages of TTS processing. For example, Hidden Markov Models are used to create parsers producing the most likely parse, or to perform labeling for speech sample databases. Decision trees are used in unit selection or in grapheme-to-phoneme algorithms, while neural networks and deep learning have emerged at the bleeding edge of TTS research.

We can consider an audio sample as a time-series of waveform sampling. By creating an auto-regressive model, it’s possible to predict the next sample. As a result, the model generates speech-kind bubbling, like a baby learning to talk by imitating sounds. If we further condition this model on the audio transcript or the pre-processing output from an existing TTS system, we get a parameterized model of speech. The output of the model describes a spectrogram for a vocoder producing actual waveforms. Because this process doesn’t rely on a database with recorded samples, but is generative, the model has a small memory footprint and allows for adjustment of parameters.

Because the model is trained on natural speech, the output retains all of its characteristics, including breathing, stresses and intonation (so neural networks can potentially solve the prosody problem). It’s possible also to adjust the pitch, create a completely different voice and even imitate singing.

At the time of this writing, Microsoft is offering its preview version of a neural network TTS (bit.ly/2PAYXWN). It provides four voices with enhanced quality and near instantaneous performance.

Speech Generation

Now that we have the tree with metadata, we turn to speech generation. Original TTS systems tried to synthesize signals by combining sinusoids. Another interesting approach was constructing a system of differential equations describing the human vocal tract as several connected tubes of different diameters and lengths. Such solutions are very compact, but unfortunately sound quite mechanical. So, as with musical synthesizers, the focus gradually shifted to solutions based on samples, which require significant space, but essentially sound natural.

To build such a system, you have to have many hours of high-quality recordings of a professional actor reading specially constructed text. This text is split into units, labeled and stored into a database. Speech generation becomes a task of selecting proper units and gluing them together.

Because you’re not synthesizing speech, you can’t significantly adjust parameters in the runtime. If you need both male and female voices or must provide regional accents (say, Scottish or Irish), they have to be recorded separately. The text must be constructed to cover all possible sound units you’ll need. And the actors must read in a neutral tone to make concatenation easier.

(Video) C# Windows Forms Text To Speech Synthesis using with Speech.Synthesis

Splitting and labeling are also non-trivial tasks. It used to be done manually, taking weeks of tedious work. Thankfully, machine learning is now being applied to this.

Unit size is probably the most important parameter for a TTS system. Obviously, by using whole sentences, we could make the most natural sounds even with correct prosody, but recording and storing that much data is impossible. Can we split it into words? Probably, but how long will it take for an actor to read an entire dictionary? And what database size limitations are we facing? On the other side, we cannot just record the alphabet—that’s sufficient only for a spelling bee contest. So usually units are selected as two three-letter groups. They’re not necessarily syllables, as groups spanning syllable borders can be glued together much better.

Now the last step. Having a database of speech units, we need to deal with concatenation. Alas, no matter how neutral the intonation was in the original recording, connecting units still requires adjustments to avoid jumps in volume, frequency and phase. This is done with digital signal processing (DSP). It can also be used to add some intonation to phrases, like raising or lowering the generated voice for assertions or questions.

Wrapping Up

In this article I covered only the .NET API. Other platforms provide similar functionality. MacOS has NSSpeechSynthesizer in Cocoa with comparable features, and most Linux distributions include the eSpeak engine. All of these APIs are accessible through native code, so you have to use C# or C++ or Swift. For cross-platform ecosystems like Python, there are some bridges like Pyttsx, but they usually have certain limitations.

Cloud vendors, on the other hand, target wide audiences, and offer services for most popular languages and platforms. While functionality is comparable across vendors, support for SSML tags can differ, so check documentation before choosing a solution.

Microsoft offers a Text-to-Speech service as part of Cognitive Services (bit.ly/2XWorku). It not only gives you 75 voices in 45 languages, but also allows you to create your own voices. For that, the service needs audio files with a corresponding transcript. You can write your text first then have someone read it, or take an existing recording and write its transcript. After uploading these datasets to Azure, a machine learning algorithm trains a model for your own unique “voice font.” A good step-by-step guide can be found at bit.ly/2VE8th4.

A very convenient way to access Cognitive Speech Services is by using the Speech Software Development Kit (bit.ly/2DDTh9I). It supports both speech recognition and speech synthesis, and is available for all major desktop and mobile platforms and most popular languages. It’s well documented and there are numerous code samples on GitHub.

TTS continues to be a tremendous help to people with special needs. For example, check out linka.su, a Web site created by a talented programmer with cerebral paralysis to help people with speech and musculoskeletal disorders, autism, or those recovering from a stroke. Knowing from personal experience what limitations they’re facing, the author created a range of applications for people who can’t type on a regular keyboard, can only select one letter at a time, or just touch a picture on a tablet. Thanks to TTS, he literally gives a voice to those who do not have one. I wish that we all, as programmers, could be that useful to others.

Ilia Smirnovhas more than 20 years of experience developing enterprise applications on major platforms, primarily in Java and .NET. For the last decade, he has specialized in simulation of financial risks. He holds three master’s degrees, FRM and other professional certifications.

Thanks to the following Microsoft technical expert for reviewing this article: Sheng Zhao (Sheng.Zhao@microsoft.com)
Sheng Zhao is principal group software engineering with STCA Speech in Beijing

Discuss this article in the MSDN Magazine forum

(Video) Create a text to speech app in c# | Easy C# speech synthesizer tutorial.


How to convert text-to-speech in VB net? ›

Text to Speech in VB.NET
  1. Step 1: Make a New WindowsFormApplication. make a new project and name it what you want.
  2. Step 2: Add a Text Box and a Button. Keep The textbox blank. Change the text of button to "Say The Text".
  3. Step 3: Code. double click the button. put this code in: ...
  4. Step 4: Run the Program. Download Here:

What are speech synthesis methods? ›

Two basic methods of speech synthesis are considered: 1) the generation of speech from stored segments, and 2) the generation of speech through continuous control of the various speech parameters individually; in the latter case, the parameters may be physiological or acoustical.

What is OCR C#? ›

Optical character recognition (OCR) API allows for application developer to extract text in the specific language from an image.

Is VB.NET outdated? ›

While the future of VB.Net is uncertain, it remains a viable market choice. Many applications still utilize Visual Basic.Net, one of the oldest programming languages. Even if numerous new technologies are on the market, it is difficult to see how they will become current trends.

Is VB.NET discontinued? ›

NET ecosystem. As of March 11, 2020, Microsoft announced that evolution of the VB.NET language has concluded.

What is the best speech to text converter? ›

The best dictation software
  • Apple Dictation for free dictation software on Apple devices.
  • Windows 10 Speech Recognition for free dictation software on Windows.
  • Dragon by Nuance for a customizable dictation app.
  • Google Docs voice typing for dictating in Google Docs.
  • Gboard for a free mobile dictation app.

Can I make my own voice TTS? ›

Custom Voice. The Cloud Text-to-Speech API now offers Custom Voices. This feature allows you to train a custom voice model using your own studio-quality audio recordings to create a unique voice. You can use your custom voice to synthesize audio using the Cloud Text-to-Speech API.

Can I create my own AI voice? ›

Creating a synthetic voice used to be a complicated and expensive process. But thanks to advances in artificial intelligence (AI), it's now possible to create high quality synthetic voices using only a recording of your own.

How to replicate someones voice? ›

One of the most popular methods is to use voice recognition software. This software can be used to create a digital copy of someone's voice by recording them speaking and then analyzing their speech patterns.

What are the 4 basic processes of speech? ›

Speech, then, is produced by an air stream from the lungs, which goes through the trachea and the oral and nasal cavities. It involves four processes: Initiation, phonation, oro-nasal process and articulation.

Is an example of speech synthesis software? ›

Some of the prominent examples of speech synthesizers are Alexa, Cortana, and Google Home.

What is speech synthesis in NLP? ›

Speech synthesis, or text-to-speech (TTS), is the computer-based creation of artificial speech from normal language text. Not to be confused with recorded audio playback, TTS is computer-generated speech formed from text.

What algorithms are used for OCR? ›

The bounding box data and image features are then passed onto Language Processing algorithms that use RNNs, LSTMs, and Transformers to decode the feature-based information into textual data. Deep learning-based OCR algorithms have two stages—the region proposal stage and the language processing stage.

How to read text from image in asp net c#? ›

Steps to Extract Text From Image in C#
  1. Use Aspose.OCR for .NET NuGet package.
  2. Include Aspose.OCR namespace reference first.
  3. Use SetLicense method to apply Aspose license.
  4. Create an object of AsposeOcr Class instance.
  5. Use RecognizeImage method to extract text from the image by applying OCR.
Jun 30, 2021

Is Aspose OCR free? ›

Write your own OCR application with just a few lines of code, or use our free online tools.

Does Windows 10 have TTS? ›

Yes. Windows 10 has an integrated free text-to-speech tool called Narrator. Using this screen reader allows the software to read aloud the text files to you, and there are plenty of customization options you can use. However, we recommend using Speechify to get even better TTS features.

Is Microsoft TTS copyrighted? ›

Microsoft has copyright on its application used in Windows Operating System.

Does Microsoft Word have TTS? ›

Speak is a built-in feature of Word, Outlook, PowerPoint, and OneNote. You can use Speak to have text read aloud in the language of your version of Office. Text-to-speech (TTS) is the ability of your computer to play back written text as spoken words.

Is .NET still relevant 2022? ›

ASP.NET (including all its versions) remains one of the internet's most searched server-side web application frameworks. It is still widely used by developers and remains a top open-source framework on GitHub.

Is .NET being phased out? ›

The long-term-support (LTS) version 3.1 of Microsoft . NET Core Framework is slated to go out of support on December 13th, 2022. Microsoft recommends upgrading . NET Core 3.1 applications to .

What has replaced Visual Basic? ›

Gambas is a name of the platform, BASIC is the language, Gambas is also the IDE and the GUI designer of Gambas programming platform. It is the one created as a complete replacement to Microsoft Visual Basic for GNU/Linux. Programs created with Gambas can run mainly on GNU/Linux.

Why use VB.NET instead of C#? ›

VB.NET uses implicit casting and makes it easier to code whereas in C# there are lot of casting and conversions needs to be done for the same lines of code. Another aspect to be noted is that the identifiers in VB.NET are not case-sensitive. 2. VB has better auto correction techniques.

Is VB easier than C#? ›

When you will go for a job in Programming then C# will be the better choice. If you first want to learn then VB could be the better choice - it depends on what is better readable for you. In both cases : what you have to learn is not the programming-language - what you have to learn is the use of the .

Is Visual Basic still relevant in 2022? ›

– Yes, absolutely! VBA is certainly not the most modern programming language, but due to the huge prevalence of Microsoft Office it is still a very relevant language in the year 2022.

Is Google speech-to-text API free? ›

Google. Google Speech-to-Text is a well known speech transcription API. Google gives users 60 minutes free transcription, with $300 in free credits for Google Cloud hosting. However, since Google only supports transcribing files already in a Google Cloud Bucket, the free credits won't get you very far.

What is the best text to speech API? ›

What is the best text to speech API?
  • IBM Watson API.
  • Rev.ai API.
  • Speechmatics API.
  • Google Speech-to-text API.
  • Robomatic.ai API.
  • Amazon Polly API.
  • Voicepods API.
  • Dialog Flow API.
Jan 21, 2021

What is the most realistic text to speech? ›

What is the most realistic text-to-speech tool? Both Amazon Polly and Speechify offer extremely accurate, lifelike, and human sounding voices. However, Amazon's complicated pricing model makes Speechify a better choice for affordable and realistic text-to-speech.

What do streamers use for TTS? ›

How to get text to speech on Twitch. Users can add TTS to their Twitch channels in two primary ways: via Streamlabs or StreamElements, which are two well-known streaming platforms that most streamers use.

Can TTS read other languages? ›

Get through books, docs, articles, PDFs, emails - anything you read - faster. Spanish text-to-speech software, also known as TTS, can read out content written in English and other languages in your language.

How can I make my own AI like Jarvis? ›

You can create a Jarvis-like AI using a free app called LINK Mark II.
Some commands you can say include:
  1. "Jarvis, open Google."
  2. "Jarvis, play music".
  3. "Jarvis, what's the weather."
  4. "Jarvis, get new email."
Nov 23, 2022

How much does it cost to build an AI algorithm? ›

The development, testing, and deployment of a similar artificial intelligence platform (MVP) would cost you anything between $20 thousand and $35 thousand.

Can 2 Humans have the same voice? ›

Although some people might sound quite a bit alike, no two voices are ever exactly alike. We each have a unique voice because so many factors work together to produce that voice.

Is there an app that copies voices? ›

Do you use AI Voice Cloning App? Replica has developed an AI that can replicate the human voice, and have built text-to-speech software to produce expressive speech. Visheo is a mobile app for creating cute and heartwarming Video Wish Cards for Christmas, New Year, birthday or just because.

Can AI copy your voice? ›

AI is being used to generate everything from images to text to artificial proteins, and now another thing has been added to the list: speech. Last week researchers from Microsoft released a paper on a new AI called VALL-E that can accurately simulate anyone's voice based on a sample just three seconds long.

What is the 3 stage model of speech production? ›

Three stages

The production of spoken language involves three major levels of processing: conceptualization, formulation, and articulation.

What are the 10 steps in the speech making process? ›

For those testing the water for the first time, the following ten steps are suggested as an easy and organized way to prepare a speech or paper.
  • Know your audience.
  • Know the occasion.
  • Select a topic.
  • Select a purpose.
  • Gather potential content.
  • Gather more content than actually used.
  • Organize content.
  • Phrase the speech.

What are the 3 systems involved in producing speech? ›

The Systems Involved in Speech Production

The respiratory system, laryngeal system, and articulatory systems are responsible for the physical manifestations of speech, and the nervous system regulates these systems on both the conscious and unconscious levels.

What is speech synthesis API? ›

The SpeechSynthesis interface of the Web Speech API is the controller interface for the speech service; this can be used to retrieve information about the synthesis voices available on the device, start and pause speech, and other commands besides. EventTarget SpeechSynthesis.

Which technique is used in speech synthesis? ›

The Concatenative speech synthesis technique is a corpus-based technique that uses some pre-recorded speech samples (words, syllables, half-syllables, phonemes, di- phones or triphones) in a database and produces the output speech by concatent- ing appropriate units based on the entered text utterances [62].

What are the 5 phases of NLP? ›

5 Phases of NLP
  • Lexical or Morphological Analysis. Lexical or Morphological Analysis is the initial step in NLP. ...
  • Syntax Analysis or Parsing. ...
  • Semantic Analysis. ...
  • Discourse Integration. ...
  • Pragmatic Analysis.
May 28, 2022

Is NLP used for text-to-speech? ›

Natural language processing (NLP) is a blend of different disciplines, ranging from computer science and computational linguistics to artificial intelligence, that is used together to analyze, extract and comprehend information derived from human language, including both text and spoken words.

Is speech synthesis a part of NLP? ›

In general terms, a Text-To-Speech synthesizer comprises of two parts; namely the Natural Language Processing (NLP) unit and the Digital Signal Processing (DSP) unit.

How to convert text-to-speech in asp net c#? ›

To convert text to speech the SpeechSynthesizer class is used.
cs code will look as follows:
  1. using System;
  2. using System. Speech. Synthesis;
  3. namespace ConvertTextToSpeech.
  4. {
  5. public partial class Default : System. Web. UI. Page.
  6. {
  7. protected void Page_Load(object sender, EventArgs e)
  8. {
Mar 8, 2015

How do I add text to a text file in C#? ›

AppendText() Method in C# with Examples. File. AppendText() is an inbuilt File class method which is used to create a StreamWriter that appends UTF-8 encoded text to an existing file else it creates a new file if the specified file does not exist.

How do I enable TTS with bits? ›

Press the Bits icon in the chat box and select the amount of Bits and preferred icon to go along with your chat message, and then add your message.

Does unity have text to speech? ›

Adding text-to-speech audio in Unity

We created a simple, one-step process and add a Play TextToSpeech Audio behavior to it. To do so, go to the Step Inspector > Behaviors > Add Behavior > Guidance > Play TextToSpeech Audio. In the text field you can write any text you want your users to hear in VR.

Can you translate speech to text? ›

Google Translate is one of the best tools to transcribe audio to text. With the Google Translate voice to text feature, you can speak in up to 10 languages, and the app will transcribe your words.

How do I convert text to speech and save as mp3? ›

Just copy past your texts in the text-box and click preview or save as audio button. You are done! Enjoy!

How to write to a text file in C# without overwriting? ›

TextWriter tsw = new StreamWriter(@"C:\Hello. txt"); //Writing text to the file. tsw. WriteLine("Hello"); //Close the file.

How do I add a .TXT file to Visual Studio? ›

Project Resource (Resx) Version:
  1. Right Click on your project.
  2. Select Properties.
  3. Goto the Resources Section.
  4. You will see a drop down in the top left corner of the Resources Secion, shown in the Screenshot below.
  5. Select "Files" from the DropDown.
  6. Click the Add Resource Button.
  7. A Select File Dialog box will be shown.
Jan 29, 2013

Can you add to a string in C#? ›

C# uses the + operator for both addition and concatenation. Remember: Numbers are added. Strings are concatenated.

Is Google TTS free for commercial use? ›

The API is free to use for both private and public projects. However, there are some restrictions and limitations to the API that users should be aware of.

Can I add my own voice to TTS? ›

Custom Voice. The Cloud Text-to-Speech API now offers Custom Voices. This feature allows you to train a custom voice model using your own studio-quality audio recordings to create a unique voice. You can use your custom voice to synthesize audio using the Cloud Text-to-Speech API.


1. c# text to speech with natural voices | Read Text to Speech using c# | Speak text in c#
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2. How to use the Speech Synthesis with C#
3. Asp .net text to speech using c#
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4. C# - Text to Speech (.Net Core)
5. Using Google API Speech Synthesis in .Net Core
6. Text to speech engine using C# .Net
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