Learning Lexicons From Speech Using a Pronunciation Mixture Model
By Ian McGraw, Ibrahim Badr, James R. Glass. 2013
53 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Signal Processing
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Citations in the corpus
- Deep Learning: Methods and Applications (2014, background): “Related work on designing the output linguistic representations for speech recognition can be found in [197] and in [241].”
- Discovering linguistic structures in speech: models and applications (2014, methodology): “We build the oracle recognizer on the same weather query corpus by following the procedure presented in [125].”
- End-to-End Speech Recognition: A Survey (2023, unknown): “Therefore,forlargeenough trainingresources,secondaryknowledgesourcesmightbecome obsolete[209],orevenharmful,incaseoferroneousinformation introduced[210],[211].”
- No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models (2017, background): “There have been many attempts in the community to fold the AM and PM into one component [1, 2].”