paper-with-me

Papers

SANTLR: Speech Annotation Toolkit for Low Resource Languages

2019-08-02 · Xinjian Li, Zhong Zhou, Siddharth Dalmia, Alan W. black, Florian Metze

While low resource speech recognition has attracted a lot of attention from the speech community, there are a few tools available to facilitate low resource speech collection. In this work, we present SANTLR: Speech Annotation Toolkit for Low Resource Languages. It is a web-based toolkit which allows researchers to easily collect and annotate a corpus of speech in a low resource language. Annotators may use this toolkit for two purposes: transcription or recording. In transcription, annotators would transcribe audio files provided by the researchers; in recording, annotators would record their voice by reading provided texts. We highlight two properties of this toolkit. First, SANTLR has a very user-friendly User Interface (UI). Both researchers and annotators may use this simple web interface to interact. There is no requirement for the annotators to have any expertise in audio or text processing. The toolkit would handle all preprocessing and postprocessing steps. Second, we employ a multi-step ranking mechanism facilitate the annotation process. In particular, the toolkit would give higher priority to utterances which are easier to annotate and are more beneficial to achieving the goal of the annotation, e.g. quickly training an acoustic model.

📄 PDF Abstract BibTeX arXiv:1908.01067

Code (0)

등록된 구현이 없습니다.

Tasks

speech-recognitionSpeech Recognition

Similar Papers 제목 키워드 기반

AnnoTheia: A Semi-Automatic Annotation Toolkit for Audio-Visual Speech Technologies

2024-02-20 · José-M. Acosta-Triana, David Gimeno-Gómez, Carlos-D. Martínez-Hinarejos

More than 7,000 known languages are spoken around the world. However, due to the lack of annotated resources, only a small fraction of them are currently covered by speech technologies. Albeit self-supervised speech repr…

Active Speaker Detection

Vakyansh: ASR Toolkit for Low Resource Indic languages

2022-03-30 · Harveen Singh Chadha, Anirudh Gupta, Priyanshi Shah, Neeraj Chhimwal 외

We present Vakyansh, an end to end toolkit for Speech Recognition in Indic languages. India is home to almost 121 languages and around 125 crore speakers. Yet most of the languages are low resource in terms of data and p…

Punctuation Restorationspeech-recognitionSpeech Recognition

Scikit-talk: A toolkit for processing real-world conversational speech data

2021-07-01 · SIGDIAL (ACL) 2021 7 · Andreas Liesenfeld, Gabor Parti, Chu-Ren Huang

We present Scikit-talk, an open-source toolkit for processing collections of real-world conversational speech in Python. First of its kind, the toolkit equips those interested in studying or modeling conversations with a…

User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis

2020-12-15 · ComputEL 2021 3 · Oliver Adams, Benjamin Galliot, Guillaume Wisniewski, Nicholas Lambourne 외

This paper reports on progress integrating the speech recognition toolkit ESPnet into Elpis, a web front-end originally designed to provide access to the Kaldi automatic speech recognition toolkit. The goal of this work …

Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition

Phonemic Representation and Transcription for Speech to Text Applications for Under-resourced Indigenous African Languages: The Case of Kiswahili

2022-10-29 · Ebbie Awino, Lilian Wanzare, Lawrence Muchemi, Barack Wanjawa 외

Building automatic speech recognition (ASR) systems is a challenging task, especially for under-resourced languages that need to construct corpora nearly from scratch and lack sufficient training data. It has emerged tha…

Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition+1