What are the speech recognition and synthesis tools available today?


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Some of the popular speech recognition and synthesis tools are:

Speech Recognition:​

1. Google Speech-to-Text - Converts speech to text. It uses neural networks to convert speech to text.

2. Wit.ai - Builds speech interfaces for any software. It is based on machine learning and natural language processing.

3. IBM Watson Speech to Text - Transcribes speech to text. It is based on deep learning and neural networks.

4. Kaldi - An open source speech recognition toolkit. It uses finite-state transducers, deep neural networks and other approaches.

Speech Synthesis:​

1. Google Text-to-Speech - Converts text to speech in over 180 voices across 30+ languages. It is based on neural networks.

2. AWS Polly - Turns text into lifelike speech. It uses neural networks to synthesize speech that sounds like a human voice.

3. CereProc - Provides natural sounding text-to-speech voices. It combines unit selection and statistical parametric synthesis techniques.

4. Nuance Vocalizer - Delivers human-like voices that bring stories and conversations to life. It is based on a machine learning algorithm trained on a large amount of data.

5. OpenTTS - An open source text-to-speech system. It uses a form of concatenative synthesis that combines pre-recorded fragments to generate speech.

The working principles of these tools are:​

1. Machine Learning and Deep Learning - Most modern systems utilize neural networks and large datasets to learn how to convert speech to text and vice versa.

2. Natural Language Processing - For speech recognition, NLP is used to understand the intent and meaning of spoken sentences. For synthesis, it generates linguistically correct speech.

3. Acoustic Modeling - Mapping speech signals to phonetic and linguistic elements. Used to recognize speech and generate speech waveforms.

4. Concatenative Synthesis - Combining pre-recorded speech fragments to generate new utterances. Used in some speech synthesis systems.

5. Statistical Parametric Synthesis - Generating speech using statistical models to determine acoustic parameters from text. Used in some speech synthesis tools.