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USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments

2021-07-30 · Muhammadjon Musaev, Saida Mussakhojayeva, Ilyos Khujayorov, Yerbolat Khassanov, Mannon Ochilov, Huseyin Atakan Varol

We present a freely available speech corpus for the Uzbek language and report preliminary automatic speech recognition (ASR) results using both the deep neural network hidden Markov model (DNN-HMM) and end-to-end (E2E) architectures. The Uzbek speech corpus (USC) comprises 958 different speakers with a total of 105 hours of transcribed audio recordings. To the best of our knowledge, this is the first open-source Uzbek speech corpus dedicated to the ASR task. To ensure high quality, the USC has been manually checked by native speakers. We first describe the design and development procedures of the USC, and then explain the conducted ASR experiments in detail. The experimental results demonstrate promising results for the applicability of the USC for ASR. Specifically, 18.1% and 17.4% word error rates were achieved on the validation and test sets, respectively. To enable experiment reproducibility, we share the USC dataset, pre-trained models, and training recipes in our GitHub repository.

📄 PDF Abstract BibTeX arXiv:2107.14419

Code (1)

IS2AI/Uzbek_ASR 공식 구현

Tasks

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

FeruzaSpeech: A 60 Hour Uzbek Read Speech Corpus with Punctuation, Casing, and Context

2024-09-23 · Anna Povey, Katherine Povey

This paper introduces FeruzaSpeech, a read speech corpus of the Uzbek language, containing transcripts in both Cyrillic and Latin alphabets, freely available for academic research purposes. This corpus includes 60 hours …

UzbekTagger: The rule-based POS tagger for Uzbek language

2023-01-30 · Maksud Sharipov, Elmurod Kuriyozov, Ollabergan Yuldashev, Ogabek Sobirov

This research paper presents a part-of-speech (POS) annotated dataset and tagger tool for the low-resource Uzbek language. The dataset includes 12 tags, which were used to develop a rule-based POS-tagger tool. The corpus…

Language Modeling Language Modelling Machine Translation POS+6

Creating a morphological and syntactic tagged corpus for the Uzbek language

2022-10-27 · Maksud Sharipov, Jamolbek Mattiev, Jasur Sobirov, Rustam Baltayev

Nowadays, creation of the tagged corpora is becoming one of the most important tasks of Natural Language Processing (NLP). There are not enough tagged corpora to build machine learning models for the low-resource Uzbek l…

POS

UzBERT: pretraining a BERT model for Uzbek

2021-08-22 · B. Mansurov, A. Mansurov

Pretrained language models based on the Transformer architecture have achieved state-of-the-art results in various natural language processing tasks such as part-of-speech tagging, named entity recognition, and question …

Language Modeling Language Modelling model named-entity-recognition+4

BBPOS: BERT-based Part-of-Speech Tagging for Uzbek

2025-01-17 · Latofat Bobojonova, Arofat Akhundjanova, Phil Ostheimer, Sophie Fellenz

This paper advances NLP research for the low-resource Uzbek language by evaluating two previously untested monolingual Uzbek BERT models on the part-of-speech (POS) tagging task and introducing the first publicly availab…

Part-Of-Speech Tagging POS POS Tagging Sensitivity