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Detect and isolate speech and other sounds

Detect speech and other sounds and locate their start and end times. For streaming applications, use a voice activity detector (VAD) to output the probability that speech is present in a given frame. You can also useSpeech-to-Text Transcriptionto create time-aligned word labels for speech signals.

Apps

Signal Labeler

Label signal attributes, regions, and points of interest, and extract features

Objects

voiceActivityDetector Detect presence of speech in audio signal

Functions

`detectSpeech`	Detect boundaries of speech in audio signal
`classifySound`	Classify sounds in audio signal

Blocks

Voice Activity Detector

Detect presence of speech in audio signal

Featured Examples

Cocktail Party Source Separation Using Deep Learning Networks

Isolate a speech signal using a deep learning network.

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Keyword Spotting in Noise Using MFCC and LSTM Networks

Identify a keyword in noisy speech using a deep learning network. In particular, the example uses a Bidirectional Long Short-Term Memory (BiLSTM) network and mel frequency cepstral coefficients (MFCC).

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Voice Activity Detection in Noise Using Deep Learning

Detect regions of speech in a low signal-to-noise environment using deep learning. The example uses the Speech Commands Dataset to train a Bidirectional Long Short-Term Memory (BiLSTM) network to detect voice activity.

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