Speech Recognition
Spectrograms, CTC, RNN-T, Conformer, Whisper, streaming, diarisation and self-supervised audio.
20concepts
140flashcards
156minutes of reading
- 01 HuBERT and Discrete Audio Units HuBERT pre-trains a speech encoder by predicting offline k-means cluster labels for masked audio frames, producing discrete unit sequences that rival phoneme transcriptions without any text supervision.
- 02 Language-Model Fusion Language-model fusion techniques inject text-only knowledge into end-to-end ASR models at inference time or training time, and the correct method depends on how much implicit language bias the acoustic model has already absorbed.
- 03 The RNN-Transducer The RNN-Transducer is a fully neural, streaming-capable sequence transduction model that replaces CTC's conditional independence assumption with a learned label-context network, enabling accurate on-device speech recognition.