4 citations · 4 across the 10 of their papers we have counts for
10 papers
SPGISpeech 2.0: Transcribed multi-speaker financial audio for speaker-tagged transcription
Raymond Grossman, Taejin Park, Kunal Dhawan +6
We introduce SPGISpeech 2.0, a dataset suitable for speaker-tagged transcription in the financial domain. SPGISpeech 2.0 improves the diversity of applicable modeling tasks while m…
Speaker Targeting via Self-Speaker Adaptation for Multi-talker ASR
Weiqing Wang, Taejin Park, Ivan Medennikov +6
We propose a self-speaker adaptation method for streaming multi-talker automatic speech recognition (ASR) that eliminates the need for explicit speaker queries. Unlike conventional…
META-CAT: Speaker-Informed Speech Embeddings via Meta Information Concatenation for Multi-talker ASR
Jinhan Wang, Weiqing Wang, Kunal Dhawan +7
We propose a novel end-to-end multi-talker automatic speech recognition (ASR) framework that enables both multi-speaker (MS) ASR and target-speaker (TS) ASR. Our proposed model is…
Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems
Taejin Park, Ivan Medennikov, Kunal Dhawan +6
Sortformer is an encoder-based speaker diarization model designed for supervising speaker tagging in speech-to-text models. Instead of relying solely on permutation invariant loss…
Resource-Efficient Adaptation of Speech Foundation Models for Multi-Speaker ASR
Weiqing Wang, Kunal Dhawan, Taejin Park +6
Speech foundation models have achieved state-of-the-art (SoTA) performance across various tasks, such as automatic speech recognition (ASR) in hundreds of languages. However, multi…
NEST: Self-supervised Fast Conformer as All-purpose Seasoning to Speech Processing Tasks
He Huang, Taejin Park, Kunal Dhawan +6
Self-supervised learning has been proved to benefit a wide range of speech processing tasks, such as speech recognition/translation, speaker verification and diarization, etc. Howe…
The CHiME-7 Challenge: System Description and Performance of NeMo Team's DASR System
Tae Jin Park, He Huang, Ante Jukic +7
We present the NVIDIA NeMo team's multi-channel speech recognition system for the 7th CHiME Challenge Distant Automatic Speech Recognition (DASR) Task, focusing on the development…
Property-Aware Multi-Speaker Data Simulation: A Probabilistic Modelling Technique for Synthetic Data Generation
Tae Jin Park, He Huang, Coleman Hooper +5
We introduce a sophisticated multi-speaker speech data simulator, specifically engineered to generate multi-speaker speech recordings. A notable feature of this simulator is its ca…
Enhancing Speaker Diarization with Large Language Models: A Contextual Beam Search Approach
Tae Jin Park, Kunal Dhawan, Nithin Koluguri +1
Large language models (LLMs) have shown great promise for capturing contextual information in natural language processing tasks. We propose a novel approach to speaker diarization…
Multi-scale Speaker Diarization with Dynamic Scale Weighting
Tae Jin Park, Nithin Rao Koluguri, Jagadeesh Balam +1
Speaker diarization systems are challenged by a trade-off between the temporal resolution and the fidelity of the speaker representation. By obtaining a superior temporal resolutio…