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Lisa van Staden Removing Nuisance Variables from Acoustic Word Embeddings Obtaining transcriptions is expensive and not always possible. Popular methods for speech processing rely on transcribed speech. 1 Low-Resource Speech and Language

  1. Lisa van Staden Removing Nuisance Variables from Acoustic Word Embeddings

  2. Obtaining transcriptions is expensive and not always possible. Popular methods for speech processing rely on transcribed speech. 1 Low-Resource Speech and Language Processing

  3. • Query-by-Example Search: search speech using speech. We don’t always need to predict text labels: • Tasks need speech segments to be compared. 2 Tasks in LSL Processing

  4. 3 We want to map speech to these representation without using labels. Acoustic Word Embeddings

  5. We want embeddings to be robust. Acoustic properties of speech from different speakers/sexes differ. 4 Nuisance Variables: Speaker and Sex

  6. 5 Current Models

  7. • Improved models: Disentanglement with adverserial training. • Using embeddings in downstream tasks. • Investigate the phonetic information in embeddings. • Links to language acquisition. 6 What’s Next

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