What is the basic pipeline of a speech recognition system?

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ICSM Computer · Answer

1. Audio Input
What happens: Captures raw speech signal via a microphone.Format: Usually a waveform (.wav, .mp3, etc.)
2. Preprocessing
Tasks:
Noise reductionVoice activity detection (removing silence)Normalization
Goal: Clean and standardize the signal for feature extraction.
3. Feature Extraction
Common techniques:
MFCC (Mel-Frequency Cepstral Coefficients)SpectrogramLog Mel-filterbanks
Purpose: Convert audio waveform into meaningful numerical features that represent phonetic content.
4. Acoustic Modeling
Models: DNN, CNN, RNN, LSTM, TransformersRole: Map features (like MFCCs) to phonetic units (phones or senones).
5. Language Modeling
Models: N-grams, RNNs, Transformer-based (like BERT, GPT)Purpose: Predict word sequences by understanding grammar and context.
6. Decoding
Process: Combines acoustic model + language model + pronunciation dictionary (lexicon) to convert the signal into text.Output: Most likely word sequence (transcription).
7. Post-processing
Includes:
Punctuation insertionCapitalizationError correction (optional)
Goal: Produce a clean and readable transcription.
End-to-End Models
Modern systems (like Whisper, DeepSpeech) use end-to-end deep learning models that skip traditional pipelines and directly map audio to text.

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What is the basic pipeline of a speech recognition system?

ICSM Computer

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1 Answers

1. Audio Input

2. Preprocessing

3. Feature Extraction

4. Acoustic Modeling

5. Language Modeling

6. Decoding

7. Post-processing

End-to-End Models

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