Andreas Stolcke

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Amazon ∙ Microsoft

Principal researcher in the Speech and Dialog Research Group at Microsoft Research,

Personalization Strategies for End-to-End Speech Recognition Systems

The recognition of personalized content, such as contact names, remains ...
02/15/2021 ∙ by Aditya Gourav, et al. ∙ 0 ∙ share

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Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding

Spoken language understanding (SLU) systems extract transcriptions, as w...
02/12/2021 ∙ by Milind Rao, et al. ∙ 0 ∙ share

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REDAT: Accent-Invariant Representation for End-to-End ASR by Domain Adversarial Training with Relabeling

Accents mismatching is a critical problem for end-to-end ASR. This paper...
12/14/2020 ∙ by Hu Hu, et al. ∙ 0 ∙ share

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BW-EDA-EEND: Streaming End-to-End Neural Speaker Diarization for a Variable Number of Speakers

We present a novel online end-to-end neural diarization system, BW-EDA-E...
11/05/2020 ∙ by Eunjung Han, et al. ∙ 0 ∙ share

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DOVER-Lap: A Method for Combining Overlap-aware Diarization Outputs

Several advances have been made recently towards handling overlapping sp...
11/03/2020 ∙ by Desh Raj, et al. ∙ 0 ∙ share

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Efficient minimum word error rate training of RNN-Transducer for end-to-end speech recognition

In this work, we propose a novel and efficient minimum word error rate (...
07/27/2020 ∙ by Jinxi Guo, et al. ∙ 0 ∙ share

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Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm

Speaker diarization based on bottom-up clustering of speech segments by ...
10/24/2019 ∙ by Andreas Stolcke, et al. ∙ 0 ∙ share

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Combining Acoustics, Content and Interaction Features to Find Hot Spots in Meetings

Involvement hot spots have been proposed as a useful concept for meeting...
10/24/2019 ∙ by Dave Makhervaks, et al. ∙ 0 ∙ share

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DOVER: A Method for Combining Diarization Outputs

Speech recognition and other natural language tasks have long benefited ...
09/17/2019 ∙ by Andreas Stolcke, et al. ∙ 0 ∙ share

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Meeting Transcription Using Virtual Microphone Arrays

We describe a system that generates speaker-annotated transcripts of mee...
05/03/2019 ∙ by Takuya Yoshioka, et al. ∙ 0 ∙ share

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Comparing Human and Machine Errors in Conversational Speech Transcription

Recent work in automatic recognition of conversational telephone speech ...
08/29/2017 ∙ by Andreas Stolcke, et al. ∙ 0 ∙ share

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Andreas Stolcke

Featured Co-authors

Shinji Watanabe

Zhuo Chen

Sanjeev Khudanpur

Michael Zeng

Takuya Yoshioka

Ariya Rastrow

Roland Maas

Xuedong Huang

Anirudh Raju

Xuesong Yang

Hu Hu

Personalization Strategies for End-to-End Speech Recognition Systems

Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding

REDAT: Accent-Invariant Representation for End-to-End ASR by Domain Adversarial Training with Relabeling

BW-EDA-EEND: Streaming End-to-End Neural Speaker Diarization for a Variable Number of Speakers

DOVER-Lap: A Method for Combining Overlap-aware Diarization Outputs

Efficient minimum word error rate training of RNN-Transducer for end-to-end speech recognition

Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm

Combining Acoustics, Content and Interaction Features to Find Hot Spots in Meetings

DOVER: A Method for Combining Diarization Outputs

Meeting Transcription Using Virtual Microphone Arrays

Comparing Human and Machine Errors in Conversational Speech Transcription