17 citations · 39 across the 5 of their papers we have counts for
4 papers · 1 filter
LSTM Acoustic Models Learn to Align and Pronounce with Graphemes
Arindrima Datta, Guanlong Zhao, Bhuvana Ramabhadran +1
Automated speech recognition coverage of the world's languages continues to expand. However, standard phoneme based systems require handcrafted lexicons that are difficult and expe…
Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model
Anjuli Kannan, Arindrima Datta, Tara N. Sainath +6
Multilingual end-to-end (E2E) models have shown great promise in expansion of automatic speech recognition (ASR) coverage of the world's languages. They have shown improvement over…
Multi-Dialect Speech Recognition With A Single Sequence-To-Sequence Model
Bo Li, Tara N. Sainath, Khe Chai Sim +6
Sequence-to-sequence models provide a simple and elegant solution for building speech recognition systems by folding separate components of a typical system, namely acoustic (AM),…
Multilingual Speech Recognition With A Single End-To-End Model
Shubham Toshniwal, Tara N. Sainath, Ron J. Weiss +4
Training a conventional automatic speech recognition (ASR) system to support multiple languages is challenging because the sub-word unit, lexicon and word inventories are typically…