Phonological and computational perspectives of Language Identification (LID) system

被引:0
|
作者
Singh, Niraj Kr. [1 ]
Poonia, Anoop Singh [2 ]
机构
[1] Vivekananda Global Univ Jaipur, Jaipur, Rajasthan, India
[2] Vivekananda Global Univ Jaipur, E&C Engn, Jaipur, Rajasthan, India
来源
2015 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION & AUTOMATION (ICCCA) | 2015年
关键词
Language Recognition; Phoneme; Prosody; Pitch and Duration; Classifier; N-GRAM; RECOGNITION; SPEECH; MODELS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Living beings inherently have the ability to differentiate languages as a part of human intelligence. Automatic LID had been a science fiction in 1970's but today, this has been deployed in practical usage. From the two classifications, text-based language recognition and spoken language recognition, the latter is comparatively challenging and has been worked in the paper. Language Recognition, generally means, the system (process) which determines the identity of the particular language. It's widely used in multilingual processing's for translation, interpretations and spoken facts retrieval. It finds place in research domain of Artificial Intelligence and security for data (information) distillation. This paper experiments for systems with two different Datasets, separately for prosody and acoustic (MFCC) based study and furthermore, their system fusion to deliver a thoughtful results.
引用
收藏
页码:223 / 226
页数:4
相关论文
共 50 条
  • [1] Computational Perspectives on Phonological Constituency and Recursion
    Kristine, M. Yu
    CATALAN JOURNAL OF LINGUISTICS, 2021, 20 : 77 - 114
  • [2] Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives
    Dinkar, Tanvi
    Clavel, Chloe
    Vasilescu, Ioana
    TRAITEMENT AUTOMATIQUE DES LANGUES, 2022, 63 (03): : 37 - 62
  • [3] Phonological memory, phonological awareness, and foreign language word learning
    Hu, CF
    LANGUAGE LEARNING, 2003, 53 (03) : 429 - 462
  • [4] BERT-LID: Leveraging BERT to Improve Spoken Language Identification
    Nie, Yuting
    Zhao, Junhong
    Zhang, Wei-Qiang
    Bai, Jinfeng
    2022 13TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING (ISCSLP), 2022, : 384 - 388
  • [5] SPOKEN LANGUAGE IDENTIFICATION USING BIDIRECTIONAL LSTM BASED LID SEQUENTIAL SENONES
    Muralikrishna, H.
    Sapra, Pulkit
    Jain, Anuksha
    Dinesh, Dileep Aroor
    2019 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU 2019), 2019, : 320 - 326
  • [6] DISTINCTIVE FEATURES OF ROMAN JAKOBSON IN THE PHONOLOGICAL SYSTEM OF THE SERBIAN LANGUAGE
    Batas, Ana S.
    NASLEDE, 2024, 20 (57):
  • [7] A hierarchical language identification system for Indian languages
    Jothilakshmi, S.
    Ramalingam, V.
    Palanivel, S.
    DIGITAL SIGNAL PROCESSING, 2012, 22 (03) : 544 - 553
  • [8] Early language experience and underspecified phonological representations
    Hunter, Cynthia R.
    Pisoni, David B.
    APPLIED PSYCHOLINGUISTICS, 2017, 38 (06) : 1325 - 1329
  • [9] LID: A Unified Model Incorporating Acoustic-Phonetic and Phonotactic Information for Language Identification
    Liu, Hexin
    Perera, Leibny Paola Garcia
    Khong, Andy W. H.
    Styles, Suzy J.
    Khudanpur, Sanjeev
    INTERSPEECH 2022, 2022, : 2233 - 2237
  • [10] Phonological memory in sign language relies on the visuomotor neural system outside the left hemisphere language network
    Kanazawa, Yuji
    Nakamura, Kimihiro
    Ishii, Toru
    Aso, Toshihiko
    Yamazaki, Hiroshi
    Omori, Koichi
    PLOS ONE, 2017, 12 (09):