Search Results for author:
Found 8 papers, 2 papers with code
META-CAT: Speaker-Informed Speech Embeddings via Meta Information Concatenation for Multi-talker ASR
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.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition
Given recent advances in generative AI technology, a key question is how large language models (LLMs) can enhance acoustic modeling tasks using text decoding results from a frozen, pretrained automatic speech recognition (ASR) model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Sortformer: Seamless Integration of Speaker Diarization and ASR by Bridging Timestamps and Tokens
We demonstrate that combining Sort Loss and PIL achieves performance competitive with state-of-the-art end-to-end diarization models trained exclusively with PIL.
Resource-Efficient Adaptation of Speech Foundation Models for Multi-Speaker ASR
Speech foundation models have achieved state-of-the-art (SoTA) performance across various tasks, such as automatic speech recognition (ASR) in hundreds of languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization
This paper presents the CHiME-8 DASR challenge which carries on from the previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge.
Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
This paper introduces a Large Language Model (LLM)-based multi-agent framework designed to enhance anomaly detection within financial market data, tackling the longstanding challenge of manually verifying system-generated anomaly alerts.
TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global context
In this paper, we propose TitaNet, a novel neural network architecture for extracting speaker representations.
Ranked #1 on
Speaker Diarization
on CALLHOME-109
Robust Multi-channel Speech Recognition using Frequency Aligned Network
In this paper, we further develop this idea and use frequency aligned network for robust multi-channel automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
