Search Results for author:
Found 30 papers, 4 papers with code
Alternative Pseudo-Labeling for Semi-Supervised Automatic Speech Recognition
Firstly, a generalized CTC loss function is introduced to handle noisy pseudo-labels by accepting alternative tokens in the positions of incorrect tokens.
Online Hybrid CTC/Attention End-to-End Automatic Speech Recognition Architecture
However, how to deploy hybrid CTC/attention systems for online speech recognition is still a non-trivial problem.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Speech Corpora Divergence Based Unsupervised Data Selection for ASR
This study proposes a unsupervised target-aware data selection method based on speech corpora divergence (SCD), which can measure the similarity between two speech corpora.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Summary on the ISCSLP 2022 Chinese-English Code-Switching ASR Challenge
Code-switching automatic speech recognition becomes one of the most challenging and the most valuable scenarios of automatic speech recognition, due to the code-switching phenomenon between multilingual language and the frequent occurrence of code-switching phenomenon in daily life.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The Conversational Short-phrase Speaker Diarization (CSSD) Task: Dataset, Evaluation Metric and Baselines
In the metric aspect, we design the new conversational DER (CDER) evaluation metric, which calculates the SD accuracy at the utterance level.
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies
Firstly, we introduce a real-time encoder states revision strategy to modify previous states.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Interrelate Training and Searching: A Unified Online Clustering Framework for Speaker Diarization
For online speaker diarization, samples arrive incrementally, and the overall distribution of the samples is invisible.
Boosting Cross-Domain Speech Recognition with Self-Supervision
The cross-domain performance of automatic speech recognition (ASR) could be severely hampered due to the mismatch between training and testing distributions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Decoupled Federated Learning for ASR with Non-IID Data
Secondly, to reduce the communication and computation costs, we propose decoupled federated learning (DecoupleFL).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Dataset
As a Mandarin speech dataset designed for dialog scenarios with high quality and rich annotations, MagicData-RAMC enriches the data diversity in the Mandarin speech community and allows extensive research on a series of speech-related tasks, including automatic speech recognition, speaker diarization, topic detection, keyword search, text-to-speech, etc.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance.
Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable
The Relation Extractor decomposes the complex question, and then the Reader answers the sub-questions in turn, and finally the Comparator performs numerical comparison and summarizes all to get the final answer, where the entire process itself constitutes a complete reasoning evidence path.
Reminding the Incremental Language Model via Data-Free Self-Distillation
Incremental language learning with pseudo-data can alleviate catastrophic forgetting in neural networks.
Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASR
In this work, in order to build a better pre-trained model for low-resource ASR, we propose a pre-training approach called wav2vec-S, where we use task-specific semi-supervised pre-training to refine the self-supervised pre-trained model for the ASR task thus more effectively utilize the capacity of the pre-trained model to generate task-specific representations for ASR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Improved Conformer-based End-to-End Speech Recognition Using Neural Architecture Search
Recently neural architecture search(NAS) has been successfully used in image classification, natural language processing, and automatic speech recognition(ASR) tasks for finding the state-of-the-art(SOTA) architectures than those human-designed architectures.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Multi-Accent Adaptation based on Gate Mechanism
To jointly train the acoustic model and the accent classifier, we propose the multi-task learning with gate mechanism (MTL-G).
A Model Compression Method with Matrix Product Operators for Speech Enhancement
In this paper, we propose a model compression method based on matrix product operators (MPO) to substantially reduce the number of parameters in DNN models for speech enhancement.
Transformer-based Online CTC/attention End-to-End Speech Recognition Architecture
To support the online recognition, we integrate the state reuse chunk-SAE and the MTA based SAD into online CTC/attention architecture.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling
This technical report describes the IOA team's submission for TASK1A of DCASE2019 challenge.
HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports
This paper describes HCCL team systems that participated in SemEval 2018 Task 8: SecureNLP (Semantic Extraction from cybersecurity reports using NLP).
HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity
In this paper, we introduce an approach to combining word embeddings and machine translation for multilingual semantic word similarity, the task2 of SemEval-2017.
Cross-Lingual Word Embeddings
Multilingual Word Embeddings
+9
Rank-1 Constrained Multichannel Wiener Filter for Speech Recognition in Noisy Environments
Multichannel linear filters, such as the Multichannel Wiener Filter (MWF) and the Generalized Eigenvalue (GEV) beamformer are popular signal processing techniques which can improve speech recognition performance.
Optimizing human-interpretable dialog management policy using Genetic Algorithm
Automatic optimization of spoken dialog management policies that are robust to environmental noise has long been the goal for both academia and industry.
Noise Robust IOA/CAS Speech Separation and Recognition System For The Third 'CHIME' Challenge
This paper presents the contribution to the third 'CHiME' speech separation and recognition challenge including both front-end signal processing and back-end speech recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
