| { | |
| "paper_id": "2020", | |
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| "generated_with": "S2ORC 1.0.0", | |
| "date_generated": "2023-01-19T04:33:40.326994Z" | |
| }, | |
| "title": "Malayalam Speech Corpus: Design and Development for Dravidian Language", | |
| "authors": [ | |
| { | |
| "first": "Elizabeth", | |
| "middle": [], | |
| "last": "Sherly", | |
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| "email": "[email protected]" | |
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| "abstract": "To overpass the disparity between theory and applications in language-related technology in the text as well as speech and several other areas, a well-designed and well-developed corpus is essential. Several problems and issues encountered while developing a corpus, especially for low resource languages. The Malayalam Speech Corpus (MSC) is one of the first open speech corpora for Automatic Speech Recognition (ASR) research to the best of our knowledge. It consists of 250 hours of Agricultural speech data. We are providing a transcription file, lexicon and annotated speech along with the audio segment. It is available in future for public use upon request at \"www.iiitmk.ac.in/vrclc/utilities/ml speechcorpus\". This paper details the development and collection process in the domain of agricultural speech corpora in the Malayalam Language.", | |
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| "text": "To overpass the disparity between theory and applications in language-related technology in the text as well as speech and several other areas, a well-designed and well-developed corpus is essential. Several problems and issues encountered while developing a corpus, especially for low resource languages. The Malayalam Speech Corpus (MSC) is one of the first open speech corpora for Automatic Speech Recognition (ASR) research to the best of our knowledge. It consists of 250 hours of Agricultural speech data. We are providing a transcription file, lexicon and annotated speech along with the audio segment. It is available in future for public use upon request at \"www.iiitmk.ac.in/vrclc/utilities/ml speechcorpus\". This paper details the development and collection process in the domain of agricultural speech corpora in the Malayalam Language.", | |
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| "section": "Abstract", | |
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| "text": "Malayalam is the official language of Kerala, Lakshadweep, and Mahe. From 1330 million people in India, 37 million people speak Malayalam ie; 2.88% of Indians. (Wikipedia contributors, 2020) . Malayalam is the youngest of all languages in the Dravidian family. Four or five decades were taken for Malayalam to emerge from Tamil. The development of Malayalam is greatly influenced by Sanskrit also.", | |
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| "start": 160, | |
| "end": 190, | |
| "text": "(Wikipedia contributors, 2020)", | |
| "ref_id": null | |
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| "section": "Introduction", | |
| "sec_num": "1." | |
| }, | |
| { | |
| "text": "In the Automatic Speech Recognition (ASR) area many works are progressing in highly and low-resourced languages. The present speech recognition system has achieved a 'Natural' degree of accuracy mainly in Standard American English (Xiong et al., 2016) . The accurate recognition of speech exists only for highly resourced languages. But it is still lagging for \"non-native\" speakers. To increase the accuracy of such an ASR system the speech data for low-resource language like Malayalam is to be increased.", | |
| "cite_spans": [ | |
| { | |
| "start": 231, | |
| "end": 251, | |
| "text": "(Xiong et al., 2016)", | |
| "ref_id": "BIBREF7" | |
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| "section": "Introduction", | |
| "sec_num": "1." | |
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| { | |
| "text": "To encourage the research on speech technology and its related applications in Malayalam, a collection of speech corpus is commissioned and named as Malayalam Speech Corpus (MSC). The corpus consists of the following parts.", | |
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| "section": "Introduction", | |
| "sec_num": "1." | |
| }, | |
| { | |
| "text": "\u2022 200 hours of Narrational Speech named NS and", | |
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| "section": "Introduction", | |
| "sec_num": "1." | |
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| "text": "\u2022 50 hours of Interview Speech named IS The raw speech data is collected from \"Kissan Krishideepam\" an agriculture-based program in Malayalam by the Department of Agriculture, Government of Kerala. The NS is created by making a script during the postproduction stage and dubbed with the help of people in different age groups and gender but they are amateur dubbing artists. The speech data is thoughtfully designed -for various applications like code mixed language analysis, Automatic Speech Recognition (ASR) related research, speaker recognition -by considering sociolinguistic variables.", | |
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| "section": "Introduction", | |
| "sec_num": "1." | |
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| "text": "Interview Speech corpora (NS and IS) collected from native Malayalam speakers. The literature survey of different speech corpora creation is detailed in section 2. Section 3 describes the design and demographics of speech data. The section 4 continues with transcription and section 5 deals with lexicon of the speech data and paper concludes with section 6.", | |
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| "section": "This paper represents the development of Narrational and", | |
| "sec_num": null | |
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| "text": "Many languages have developed speech corpus and they are open source too. The English read speech corpus is freely available to download for research purposes (Koh et al., 2019) (Panayotov et al., 2015) . Similarly, a database is made available with the collection of TED talks in the English language (Hernandez et al., 2018) . Databases are available for Indian languages on free download and a payment basis also. For the Malayalam language-based emotion recognition, a database is available (Rajan et al., 2019) .", | |
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| "end": 177, | |
| "text": "(Koh et al., 2019)", | |
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| "text": "(Panayotov et al., 2015)", | |
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| "text": "(Hernandez et al., 2018)", | |
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| "text": "(Rajan et al., 2019)", | |
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| "section": "Literature Survey", | |
| "sec_num": "2." | |
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| "text": "The corpus collection of low resourced languages is a good initiative in the area of ASR. One of such work is done on Latvian language (Pinnis et al., 2014) . They created 100 hours of orthographically transcribed audio data and annotated corpus also. In addition to that a four hours of phonetically transcribed audio data is also available. The authors presented the statistics of speech corpus along with criteria for design of speech corpus.", | |
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| "text": "(Pinnis et al., 2014)", | |
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| "section": "Literature Survey", | |
| "sec_num": "2." | |
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| "text": "South Africa has eleven official languages. An attempt is made for the creation of speech corpora on these under resourced languages (Barnard et al., 2014) . A collection of more than 50 hours of speech in each language is made available. They validated the corpora by building acoustic and language model using KALDI.", | |
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| "start": 133, | |
| "end": 155, | |
| "text": "(Barnard et al., 2014)", | |
| "ref_id": "BIBREF0" | |
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| "section": "Literature Survey", | |
| "sec_num": "2." | |
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| { | |
| "text": "Similarly speech corpora for North-East Indian lowresourced languages is also created (Hernandez et al., 2018) . The authors collected speech and text corpora on Assamese, Bengali and Nepali. They conducted a statisti-cal study of the corpora also.", | |
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| "start": 86, | |
| "end": 110, | |
| "text": "(Hernandez et al., 2018)", | |
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| "section": "Literature Survey", | |
| "sec_num": "2." | |
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| "text": "A recording studio is setup at our visual media lab with a quiet and sound proof room. A standing microphone is used for recording NS corpora. IS corpora is collected directly from the farmers using recording portable Mic at their place. Hundred speakers are involved in the recording of NS and IS corpora.", | |
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| "section": "The Speech Corpora", | |
| "sec_num": "3." | |
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| { | |
| "text": "The written agricultural script, which is phonetically balanced and phonetically rich (up to triphone model), was given to the speakers to record the Narrational Speech. Scripts were different in content. An example script is provided in Fig:1 . They were given enough time to record the data. If any recording issues happened, after rectification by the recording assistant it was rerecorded. The Narrational Speech is less expensive than Interview Speech because it is difficult to get data for the ASR system. The IS data is collected in a face-to-face interview style. The literacy and the way to communicate information fluently have given less focus. The interviewee with enough experience in his field of cultivation is asked to speak about his cultivation and its features. The interviewer should be preferably a subject expert in the area of cultivation. Both of them are given separate microphones for this purpose.", | |
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| "start": 238, | |
| "end": 243, | |
| "text": "Fig:1", | |
| "ref_id": "FIGREF0" | |
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| "section": "Narrational and Interview Speech Corpora", | |
| "sec_num": "3.1." | |
| }, | |
| { | |
| "text": "Few challenges were faced during the recording of the speech corpus. There were lot of background noise like sounds of vehicles, animals, birds, irrigation motor and wind. Another main issue that happened during post production is the difference in pronunciation styles in the Interview Speech corpora collection. This caused difficulty during validation of the corpus. The recording used to extend up to 5-6 hours depending on speakers. The recorded data is then given for post-production to clean unwanted information from that.", | |
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| "section": "Narrational and Interview Speech Corpora", | |
| "sec_num": "3.1." | |
| }, | |
| { | |
| "text": "We have set a few criteria for recording the Narrational Speech data.", | |
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| "section": "Speaker Criteria", | |
| "sec_num": "3.2." | |
| }, | |
| { | |
| "text": "\u2022 The speakers are at minimum age of 18", | |
| "cite_spans": [], | |
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| "section": "Speaker Criteria", | |
| "sec_num": "3.2." | |
| }, | |
| { | |
| "text": "\u2022 They are citizens of India", | |
| "cite_spans": [], | |
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| "section": "Speaker Criteria", | |
| "sec_num": "3.2." | |
| }, | |
| { | |
| "text": "\u2022 Speakers are residents of Kerala", | |
| "cite_spans": [], | |
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| "section": "Speaker Criteria", | |
| "sec_num": "3.2." | |
| }, | |
| { | |
| "text": "\u2022 The mother tongue of the speaker should be Malayalam without any specific accents", | |
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| "section": "Speaker Criteria", | |
| "sec_num": "3.2." | |
| }, | |
| { | |
| "text": "Speech data is collected with two different microphones for NS and IS. For Narrational Speech, Shure SM58-LC cardioid vocal microphone without cable is used. For IS, we utilized Sennheiser XSW 1-ME2-wireless presentation microphone of range 548-572 MHz Steinberg Nuendo and Pro Tools are used for the audio post-production process.", | |
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| "section": "Recording Specifications", | |
| "sec_num": "3.3." | |
| }, | |
| { | |
| "text": "The audio is recorded in 48 kHz sampling frequency and 16 bit sampling rate for broadcasting and the same is down sampled to 16 kHz sampling frequency and 16 bit sampling rate for speech-related research purposes. The recordings of speech corpora are saved in WAV files.", | |
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| "section": "Recording Specifications", | |
| "sec_num": "3.3." | |
| }, | |
| { | |
| "text": "MSC aims to present a good quality audio recording for speech related research. The NS and IS corpus have both male and female speakers. In NS, the male and female speakers are made up with 75% and 25% respectively. IS have more male speakers than females with 82% and 18% of total speakers. ", | |
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| "section": "Demographics", | |
| "sec_num": "3.4." | |
| }, | |
| { | |
| "text": "The NS and IS corpora are transcribed orthographically into Malayalam text. The transcribers are provided with the audio segments that the speaker read. Their task is to transcribe the content of the audio into Malayalam and into phonetic text. A sample of three transcribed data with demographic details is shown below and the annotated speech of first two sentences is depicted in In the first sample a Narrational Speech is detailed. The narrator is about 45 years old and he is describing the details about Palakkad a district in Kerala and a mango estate there. Few sentences are displayed below. ", | |
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| "section": "Transcription", | |
| "sec_num": "4." | |
| }, | |
| { | |
| "text": "The pronunciation dictionary, called Lexicon contains a collection of unique 4925 words. The audio collection process is still going on which will increase the lexicon size. The lexicon consists of word and its corresponding phonemic and syllabic representation as in the example shown in ", | |
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| "section": "Lexicon", | |
| "sec_num": "5." | |
| }, | |
| { | |
| "text": "Speech is the primary and natural mode of communication than writing. It is possible to extract more linguistic information from speech than text like emotions and accent. Speech related applications are more useful for illiterate and old people. The articulatory and acoustic information can be obtained from a good audio recording environment. One of the important features of speech data is that, there is less interference from a second party compared to textual data.", | |
| "cite_spans": [], | |
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| "section": "Conclusion", | |
| "sec_num": "6." | |
| }, | |
| { | |
| "text": "To encourage the academic research in speech related applications, a good number of multilingual and multipurpose speech corpora for Indian languages is required. The responsibility to develop such corpora still lies on the shoulder of the concerned researcher. Also the role of language corpora is very significant to preserve and maintain the linguistic heritage of our country.", | |
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| "section": "Conclusion", | |
| "sec_num": "6." | |
| }, | |
| { | |
| "text": "The release of MSC will be one of the first speech corpora of Malayalam, contributing 200 hours of Narrational Speech and 50 hours of Interview Speech data for public use. The lexicon and annotated speech is also made available with the data. Future work includes creation of corpora related to tourism and entertainment domains and enhancement of quality of speech by building an ASR using KALDI toolkit. The updates on corpus will be accessible through \"www.iiitmk.ac.in/vrclc/utilities/ml speechcorpus\".", | |
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| "section": "Conclusion", | |
| "sec_num": "6." | |
| } | |
| ], | |
| "back_matter": [ | |
| { | |
| "text": "This research is supported by the Kerala State Council for Science, Technology and Environment (KSCSTE). I thank KSCSTE for funding the project under the Back-to-lab scheme. I also thank Agri team, Indian Institute of Information Technology and Management-Kerala, Kissan Project for collecting the audio data.", | |
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| "section": "Acknowledgements", | |
| "sec_num": null | |
| } | |
| ], | |
| "bib_entries": { | |
| "BIBREF0": { | |
| "ref_id": "b0", | |
| "title": "The nchlt speech corpus of the south african languages", | |
| "authors": [ | |
| { | |
| "first": "E", | |
| "middle": [], | |
| "last": "Barnard", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "M", | |
| "middle": [ | |
| "H" | |
| ], | |
| "last": "Davel", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "C", | |
| "middle": [], | |
| "last": "Van Heerden", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "F", | |
| "middle": [], | |
| "last": "De Wet", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [], | |
| "last": "Badenhorst", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2014, | |
| "venue": "Workshop Spoken Language Technologies for Under-resourced Languages (SLTU)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Barnard, E., Davel, M. H., van Heerden, C., De Wet, F., and Badenhorst, J. (2014). The nchlt speech corpus of the south african languages. In Workshop Spoken Language Technologies for Under-resourced Languages (SLTU).", | |
| "links": null | |
| }, | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Ted-lium 3: twice as much data and corpus repartition for experiments on speaker adaptation", | |
| "authors": [ | |
| { | |
| "first": "F", | |
| "middle": [], | |
| "last": "Hernandez", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "V", | |
| "middle": [], | |
| "last": "Nguyen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [], | |
| "last": "Ghannay", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "N", | |
| "middle": [], | |
| "last": "Tomashenko", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Y", | |
| "middle": [], | |
| "last": "Est\u00e8ve", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2018, | |
| "venue": "International Conference on Speech and Computer", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "198--208", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Hernandez, F., Nguyen, V., Ghannay, S., Tomashenko, N., and Est\u00e8ve, Y. (2018). Ted-lium 3: twice as much data and corpus repartition for experiments on speaker adap- tation. In International Conference on Speech and Com- puter, pages 198-208. Springer.", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "Building the singapore english national speech corpus", | |
| "authors": [ | |
| { | |
| "first": "J", | |
| "middle": [ | |
| "X" | |
| ], | |
| "last": "Koh", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "A", | |
| "middle": [], | |
| "last": "Mislan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [], | |
| "last": "Khoo", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "B", | |
| "middle": [], | |
| "last": "Ang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "W", | |
| "middle": [], | |
| "last": "Ang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "C", | |
| "middle": [], | |
| "last": "Ng", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "Y.-Y", | |
| "middle": [], | |
| "last": "Tan", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2019, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "19--22", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Koh, J. X., Mislan, A., Khoo, K., Ang, B., Ang, W., Ng, C., and Tan, Y.-Y. (2019). Building the singapore english national speech corpus. Malay, 20(25.0):19-3.", | |
| "links": null | |
| }, | |
| "BIBREF3": { | |
| "ref_id": "b3", | |
| "title": "Librispeech: an asr corpus based on public domain audio books", | |
| "authors": [ | |
| { | |
| "first": "V", | |
| "middle": [], | |
| "last": "Panayotov", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "G", | |
| "middle": [], | |
| "last": "Chen", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "D", | |
| "middle": [], | |
| "last": "Povey", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [], | |
| "last": "Khudanpur", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2015, | |
| "venue": "2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "5206--5210", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Panayotov, V., Chen, G., Povey, D., and Khudanpur, S. (2015). Librispeech: an asr corpus based on public do- main audio books. In 2015 IEEE International Con- ference on Acoustics, Speech and Signal Processing (ICASSP), pages 5206-5210. IEEE.", | |
| "links": null | |
| }, | |
| "BIBREF4": { | |
| "ref_id": "b4", | |
| "title": "Designing the latvian speech recognition corpus", | |
| "authors": [ | |
| { | |
| "first": "M", | |
| "middle": [], | |
| "last": "Pinnis", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "I", | |
| "middle": [], | |
| "last": "Auzina", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "K", | |
| "middle": [], | |
| "last": "Goba", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2014, | |
| "venue": "LREC", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "1547--1553", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Pinnis, M., Auzina, I., and Goba, K. (2014). Designing the latvian speech recognition corpus. In LREC, pages 1547-1553.", | |
| "links": null | |
| }, | |
| "BIBREF5": { | |
| "ref_id": "b5", | |
| "title": "Design and development of a multi-lingual speech corpora (tamar-emodb) for emotion analysis", | |
| "authors": [ | |
| { | |
| "first": "R", | |
| "middle": [], | |
| "last": "Rajan", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "U", | |
| "middle": [], | |
| "last": "Haritha", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "A", | |
| "middle": [], | |
| "last": "Sujitha", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "T", | |
| "middle": [], | |
| "last": "Rejisha", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2019, | |
| "venue": "Proc. Interspeech 2019", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "3267--3271", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Rajan, R., Haritha, U., Sujitha, A., and Rejisha, T. (2019). Design and development of a multi-lingual speech cor- pora (tamar-emodb) for emotion analysis. Proc. Inter- speech 2019, pages 3267-3271.", | |
| "links": null | |
| }, | |
| "BIBREF6": { | |
| "ref_id": "b6", | |
| "title": "Malayalam -Wikipedia, the free encyclopedia", | |
| "authors": [], | |
| "year": 2020, | |
| "venue": "Wikipedia contributors", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Wikipedia contributors. (2020). Malayalam -Wikipedia, the free encyclopedia. [Online; accessed 21-February- 2020].", | |
| "links": null | |
| }, | |
| "BIBREF7": { | |
| "ref_id": "b7", | |
| "title": "Achieving human parity in conversational speech recognition", | |
| "authors": [ | |
| { | |
| "first": "W", | |
| "middle": [], | |
| "last": "Xiong", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "J", | |
| "middle": [], | |
| "last": "Droppo", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "X", | |
| "middle": [], | |
| "last": "Huang", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "F", | |
| "middle": [], | |
| "last": "Seide", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "M", | |
| "middle": [], | |
| "last": "Seltzer", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "A", | |
| "middle": [], | |
| "last": "Stolcke", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "D", | |
| "middle": [], | |
| "last": "Yu", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "G", | |
| "middle": [], | |
| "last": "Zweig", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2016, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": { | |
| "arXiv": [ | |
| "arXiv:1610.05256" | |
| ] | |
| }, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Xiong, W., Droppo, J., Huang, X., Seide, F., Seltzer, M., Stolcke, A., Yu, D., and Zweig, G. (2016). Achiev- ing human parity in conversational speech recognition. arXiv preprint arXiv:1610.05256.", | |
| "links": null | |
| } | |
| }, | |
| "ref_entries": { | |
| "FIGREF0": { | |
| "type_str": "figure", | |
| "num": null, | |
| "uris": null, | |
| "text": "Example of script file for dubbing" | |
| }, | |
| "FIGREF1": { | |
| "type_str": "figure", | |
| "num": null, | |
| "uris": null, | |
| "text": "Fig 2." | |
| }, | |
| "FIGREF2": { | |
| "type_str": "figure", | |
| "num": null, | |
| "uris": null, | |
| "text": "An example of Annotated Speech Corpora Sample 1: Record Entry No : 180220 01 01" | |
| }, | |
| "FIGREF4": { | |
| "type_str": "figure", | |
| "num": null, | |
| "uris": null, | |
| "text": "Example of the lexicon" | |
| }, | |
| "TABREF1": { | |
| "html": null, | |
| "type_str": "table", | |
| "content": "<table/>", | |
| "num": null, | |
| "text": "" | |
| }, | |
| "TABREF2": { | |
| "html": null, | |
| "type_str": "table", | |
| "content": "<table><tr><td>Place of Cultivation (District wise)</td><td>IS(%)</td></tr><tr><td>Thiruvananthapuram</td><td>26</td></tr><tr><td>Kollam</td><td>21</td></tr><tr><td>Pathanamthitta</td><td>02</td></tr><tr><td>Ernakulam</td><td>07</td></tr><tr><td>Alappuzha</td><td>08</td></tr><tr><td>Kottayam</td><td>08</td></tr><tr><td>Idukki</td><td>09</td></tr><tr><td>Thrissur</td><td>12</td></tr><tr><td>Wayanad</td><td>03</td></tr><tr><td>Kozhikode</td><td>02</td></tr><tr><td>Kannur</td><td>02</td></tr><tr><td>Total</td><td>100</td></tr></table>", | |
| "num": null, | |
| "text": "and 3 contains the details of the place of cultivation and the type of cultivation in Kerala." | |
| }, | |
| "TABREF3": { | |
| "html": null, | |
| "type_str": "table", | |
| "content": "<table><tr><td colspan=\"2\">: Demographic details of speakers by place of culti-</td></tr><tr><td>vation</td><td/></tr><tr><td>Type of Cultivation</td><td>IS (%)</td></tr><tr><td>Animal Husbandry</td><td>10</td></tr><tr><td>Apiculture</td><td>11</td></tr><tr><td>Diary</td><td>16</td></tr><tr><td>Fish and crab farming</td><td>05</td></tr><tr><td>Floriculture</td><td>07</td></tr><tr><td>Fruits and vegetables</td><td>22</td></tr><tr><td>Horticulture</td><td>04</td></tr><tr><td>Mixed farming</td><td>07</td></tr><tr><td>Organic farming</td><td>08</td></tr><tr><td>Poultry</td><td>07</td></tr><tr><td>Terrace farming</td><td>03</td></tr><tr><td>Total</td><td>100</td></tr></table>", | |
| "num": null, | |
| "text": "" | |
| }, | |
| "TABREF4": { | |
| "html": null, | |
| "type_str": "table", | |
| "content": "<table/>", | |
| "num": null, | |
| "text": "Demographic details of speakers by type of cultivation" | |
| } | |
| } | |
| } | |
| } |