@inproceedings{bansal-2020-acoustic,
    title = "Acoustic-Phonetic Approach for {ASR} of Less Resourced Languages Using Monolingual and Cross-Lingual Information",
    author = "Bansal, Shweta",
    editor = "Beermann, Dorothee  and
      Besacier, Laurent  and
      Sakti, Sakriani  and
      Soria, Claudia",
    booktitle = "Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources association",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.sltu-1.23/",
    pages = "167--171",
    language = "eng",
    ISBN = "979-10-95546-35-1",
    abstract = "The exploration of speech processing for endangered languages has substantially increased in the past epoch of time. In this paper, we present the acoustic-phonetic approach for automatic speech recognition (ASR) using monolingual and cross-lingual information with application to under-resourced Indian languages, Punjabi, Nepali and Hindi. The challenging task while developing the ASR was the collection of the acoustic corpus for under-resourced languages. We have described here, in brief, the strategies used for designing the corpus and also highlighted the issues pertaining while collecting data for these languages. The bootstrap GMM-UBM based approach is used, which integrates pronunciation lexicon, language model and acoustic-phonetic model. Mel Frequency Cepstral Coefficients were used for extracting the acoustic signal features for training in monolingual and cross-lingual settings. The experimental result shows the overall performance of ASR for cross-lingual and monolingual. The phone substitution plays a key role in the cross-lingual as well as monolingual recognition. The result obtained by cross-lingual recognition compared with other baseline system and it has been found that the performance of the recognition system is based on phonemic units . The recognition rate of cross-lingual generally declines as compared with the monolingual."
}