Search Results for author:
Found 13 papers, 3 papers with code
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio
This paper introduces GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10, 000 hours of high quality labeled audio suitable for supervised training, and 40, 000 hours of total audio suitable for semi-supervised and unsupervised training.
Ranked #1 on
Speech Recognition
on GigaSpeech
Adversarial Attacks and Defenses for Speech Recognition Systems
We investigate two threat models: a denial-of-service scenario where fast gradient-sign method (FGSM) or weak projected gradient descent (PGD) attacks are used to degrade the model's word error rate (WER); and a targeted scenario where a more potent imperceptible attack forces the system to recognize a specific phrase.
CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings
Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6).
Multi-task self-supervised learning for Robust Speech Recognition
We then propose a revised encoder that better learns short- and long-term speech dynamics with an efficient combination of recurrent and convolutional networks.
Induced Inflection-Set Keyword Search in Speech
We investigate the problem of searching for a lexeme-set in speech by searching for its inflectional variants.
DiPCo -- Dinner Party Corpus
We present a speech data corpus that simulates a "dinner party" scenario taking place in an everyday home environment.
Low-Resource Contextual Topic Identification on Speech
In topic identification (topic ID) on real-world unstructured audio, an audio instance of variable topic shifts is first broken into sequential segments, and each segment is independently classified.
The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines
The CHiME challenge series aims to advance robust automatic speech recognition (ASR) technology by promoting research at the interface of speech and language processing, signal processing , and machine learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages
Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve end-uses such as audio content categorization and search.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Using of heterogeneous corpora for training of an ASR system
The paper summarizes the development of the LVCSR system built as a part of the Pashto speech-translation system at the SCALE (Summer Camp for Applied Language Exploration) 2015 workshop on "Speech-to-text-translation for low-resource languages".
Topic Identification for Speech without ASR
Modern topic identification (topic ID) systems for speech use automatic speech recognition (ASR) to produce speech transcripts, and perform supervised classification on such ASR outputs.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
New release of Mixer-6: Improved validity for phonetic study of speaker variation and identification
The Mixer series of speech corpora were collected over several years, principally to support annual NIST evaluations of speaker recognition (SR) technologies.
