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eess.AS2024

Boosting Hybrid Autoregressive Transducer-based ASR with Internal Acoustic Model Training and Dual Blank Thresholding

Takafumi Moriya, Takanori Ashihara, Masato Mimura +4

A hybrid autoregressive transducer (HAT) is a variant of neural transducer that models blank and non-blank posterior distributions separately. In this paper, we propose a novel int…

eess.AS2024

Alignment-Free Training for Transducer-based Multi-Talker ASR

Takafumi Moriya, Shota Horiguchi, Marc Delcroix +5

Extending the RNN Transducer (RNNT) to recognize multi-talker speech is essential for wider automatic speech recognition (ASR) applications. Multi-talker RNNT (MT-RNNT) aims to ach…

eess.AS2024

NTT Multi-Speaker ASR System for the DASR Task of CHiME-8 Challenge

Naoyuki Kamo, Naohiro Tawara, Atsushi Ando +15

We present a distant automatic speech recognition (DASR) system developed for the CHiME-8 DASR track. It consists of a diarization first pipeline. For diarization, we use end-to-en…

cs.CL2024

Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation

Kohei Matsuura, Takanori Ashihara, Takafumi Moriya +4

This paper introduces a novel approach called sentence-wise speech summarization (Sen-SSum), which generates text summaries from a spoken document in a sentence-by-sentence manner.…

eess.AS2024

SpeakerBeam-SS: Real-time Target Speaker Extraction with Lightweight Conv-TasNet and State Space Modeling

Hiroshi Sato, Takafumi Moriya, Masato Mimura +6

Real-time target speaker extraction (TSE) is intended to extract the desired speaker's voice from the observed mixture of multiple speakers in a streaming manner. Implementing real…