Search Results for author:
Found 22 papers, 4 papers with code
FINDINGS OF THE IWSLT 2021 EVALUATION CAMPAIGN
The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2021) featured this year four shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Multilingual speech translation, (iv) Low-resource speech translation.
JHU IWSLT 2022 Dialect Speech Translation System Description
This paper details the Johns Hopkins speech translation (ST) system used in the IWLST2022 dialect speech translation task.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
On Speaker Attribution with SURT
The Streaming Unmixing and Recognition Transducer (SURT) has recently become a popular framework for continuous, streaming, multi-talker speech recognition (ASR).
Speech collage: code-switched audio generation by collaging monolingual corpora
Designing effective automatic speech recognition (ASR) systems for Code-Switching (CS) often depends on the availability of the transcribed CS resources.
The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
We introduce HK-LegiCoST, a new three-way parallel corpus of Cantonese-English translations, containing 600+ hours of Cantonese audio, its standard traditional Chinese transcript, and English translation, segmented and aligned at the sentence level.
Bypass Temporal Classification: Weakly Supervised Automatic Speech Recognition with Imperfect Transcripts
Imperfectly transcribed speech is a prevalent issue in human-annotated speech corpora, which degrades the performance of ASR models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Towards Zero-Shot Code-Switched Speech Recognition
In this work, we seek to build effective code-switched (CS) automatic speech recognition systems (ASR) under the zero-shot setting where no transcribed CS speech data is available for training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Injecting Text and Cross-lingual Supervision in Few-shot Learning from Self-Supervised Models
Self-supervised model pre-training has recently garnered significant interest, but relatively few efforts have explored using additional resources in fine-tuning these models.
End-to-end ASR to jointly predict transcriptions and linguistic annotations
We propose a Transformer-based sequence-to-sequence model for automatic speech recognition (ASR) capable of simultaneously transcribing and annotating audio with linguistic information such as phonemic transcripts or part-of-speech (POS) tags.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
The Multilingual TEDx Corpus for Speech Recognition and Translation
We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages.
A Corpus for Large-Scale Phonetic Typology
A major hurdle in data-driven research on typology is having sufficient data in many languages to draw meaningful conclusions.
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.
Massively Multilingual Adversarial Speech Recognition
We report on adaptation of multilingual end-to-end speech recognition models trained on as many as 100 languages.
Pretraining by Backtranslation for End-to-end ASR in Low-Resource Settings
Using transcribed speech from nearby languages gives a further 20-30% relative reduction in character error rate.
Analysis of Multilingual Sequence-to-Sequence speech recognition systems
This paper investigates the applications of various multilingual approaches developed in conventional hidden Markov model (HMM) systems to sequence-to-sequence (seq2seq) automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling
In this work, we attempt to use data from 10 BABEL languages to build a multi-lingual seq2seq model as a prior model, and then port them towards 4 other BABEL languages using transfer learning approach.
Language Modelling
Sequence-To-Sequence Speech Recognition
+2
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.
ESPnet: End-to-End Speech Processing Toolkit
This paper introduces a new open source platform for end-to-end speech processing named ESPnet.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multi-Modal Data Augmentation for End-to-End ASR
We present a new end-to-end architecture for automatic speech recognition (ASR) that can be trained using \emph{symbolic} input in addition to the traditional acoustic input.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
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
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
