5 papers · 2 filters
HINTT Submission to the 2nd MLC-SLM Challenge: Comparing Cascaded and Unified Approaches to Diarization and ASR
Takanori Ashihara, Kohei Matsuura, Masato Mimura
This paper presents the HINTT system submitted to the 2nd Challenge and Workshop on Multilingual Conversational Speech Language Model (MLC-SLM). We address multilingual speaker-att…
Improving Large-Scale Weakly Supervised ASR by Filtering and Selection
Kohei Matsuura, Masato Mimura
Leveraging large-scale weakly supervised datasets is crucial to train robust end-to-end automatic speech recognition (ASR) models. However, such datasets often contain noisy labels…
Progressive Alignment Objectives for Aligner-Encoder based ASR
Jaeyoung Lee, Masato Mimura, Takafumi Moriya
Aligner-Encoders are recently proposed seq2seq end-to-end ASR models that replace decoder attention by predicting the uth token directly from the u-th encoder position, so the enco…
Chunkwise Aligners for Streaming Speech Recognition
Wen Shen Teo, Takafumi Moriya, Masato Mimura
We propose the Chunkwise Aligner, a novel architecture for streaming automatic speech recognition (ASR). While the Transducer is the standard model for streaming ASR, its training…
Decoder-only Conformer with Modality-aware Sparse Mixtures of Experts for ASR
Jaeyoung Lee, Masato Mimura
We present a decoder-only Conformer for automatic speech recognition (ASR) that processes speech and text in a single stack without external speech encoders or pretrained large lan…