We have seen many posts on Object detections, Autonomous cars, Stylized Paintings, Natural Language Processing, etc. However, we never touched few areas on Artificial Intelligence, Machine Learning, Deep Learning.
Today, we are going to get a little deeper into the Speech Deep Learning toolkit.
What is SpeechBrain?
SpeechBrain is an open-source toolkit based on Pytorch developed exclusively for Speech technology.
What are SpeechBrain Toolkit supports?
- Speech Recognition: Speech-to-text
- Speaker Recognition: Speaker verification/ID
- Speaker Diarization: Detect who spoke when.
- Speech Enhancement: Noisy to clean speech
- Speech Separation: Separate overlapped speech
- Spoken Language Understanding: Speech to intent/slots.
- Multi-microphone processing: Combining input signals
SpeechBrain solves the following types of problems
- Speech classification (many-to-one, e.g., speaker-id)
- Speech regression (speech-to-speech mapping, e.g., speech enhancement)
- Sequence-to-Sequence (speech to speech mapping, e.g., speech recognition)
SpeechBrain Pretrained Models
- Speech Recognition in different languages
- Speech Separation
- Speaker Verification
- Speech Enhancement
- Command Recognition
- Spoken Language Understanding
- Urban Sound Classification
We will go into detail about a few of the SpeechBrain codes in the next posts.
Stay Tuned!
Have anyone tried SpeechBrain?
Would you please comment below?
Further Reading
Posts on Artificial Intelligence, Deep Learning, Machine Learning, and Design Thinking articles:
Artificial Intelligence Chatbot Using Neural Network and Natural Language Processing
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