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20192024
most citedStreaming Multi-speaker ASR with RNN-T

3 citations · 7 across the 5 of their papers we have counts for

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6 papers · 1 filter

eess.AS2024★ 1 cited

Anatomy of Industrial Scale Multilingual ASR

Francis McCann Ramirez, Luka Chkhetiani, Andrew Ehrenberg +14

This paper describes AssemblyAI's industrial-scale automatic speech recognition (ASR) system, designed to meet the requirements of large-scale, multilingual ASR serving various app…

eess.AS2024★ 3 cited

Two-pass Endpoint Detection for Speech Recognition

Anirudh Raju, Aparna Khare, Di He +9

Endpoint (EP) detection is a key component of far-field speech recognition systems that assist the user through voice commands. The endpoint detector has to trade-off between accur…

eess.AS2022

Separator-Transducer-Segmenter: Streaming Recognition and Segmentation of Multi-party Speech

Ilya Sklyar, Anna Piunova, Christian Osendorfer

Streaming recognition and segmentation of multi-party conversations with overlapping speech is crucial for the next generation of voice assistant applications. In this work we addr…

eess.AS2020★ 3 cited

Streaming Multi-speaker ASR with RNN-T

Ilya Sklyar, Anna Piunova, Yulan Liu

Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers. However, all published works have assumed no latency constraints during inferen…

eess.AS2020

Improving RNN-T ASR Accuracy Using Context Audio

Andreas Schwarz, Ilya Sklyar, Simon Wiesler

We present a training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to learn to exp…

eess.AS2020

Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition

Egor Lakomkin, Jahn Heymann, Ilya Sklyar +1

Subwords are the most widely used output units in end-to-end speech recognition. They combine the best of two worlds by modeling the majority of frequent words directly and at the…