Shikhamoni Nath | North Eastern Regional Institute of Science and Technology (original) (raw)

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Papers by Shikhamoni Nath

The primary objective of speech signal is the transfer of linguistic message. However, the acoust... more The primary objective of speech signal is the transfer of linguistic message. However, the acoustic signal also contains auxiliary information related to language, speaker, acoustic environment etc. Automatic recognition of the language of speech signal is not only scientifically interesting but also of technological importance in a multilingual country such as India. While a few language identification systems in the context of Indian languages have been implemented, most such systems have used small scale speech data collected internally within the organization. Recently, the Babel program of IARPA has released challenging speech data in three Indian languages: Assamese, Bengali and Tamil. Here, we report the development of an automatic language identification (LID) system that recognises the language of a given speech signal in any of these 3 languages. The LID system is built as an layer over the Automatic Speech Recognition (ASR) systems of these 3 languages trained using the B...

IEEE Systems Journal, 2018

Collaborative sensing helps in achieving a more accurate sensing decision than individual sensing... more Collaborative sensing helps in achieving a more accurate sensing decision than individual sensing in cognitive radio network (CRN). In an infrastructure-based CRN, each node sends its local sensing report to the fusion center (FC), which uses a fusion rule to aggregate the local sensing reports. However, collaborative sensing is vulnerable to the spectrum sensing data falsification attack, in which a node falsifies its local sensing report before sending it to the FC with the intention of disrupting the final sensing decision of the FC. In practice, the strategy of an attacker is not known. However, the collection of sensing reports at the FC can be useful for data mining with the objective of identifying the attackers. In this paper, we present a method that uses clustering techniques for detection and isolation of such attackers. We employ two clustering techniques, viz., K-medoids clustering and agglomerative hierarchical clustering. Unlike threshold detection that requires some predefined threshold value as input, the proposed approach detects the attackers using only the collection of sensing reports at the FC. We also present how we can use the proposed approach on streaming data (sensing reports), and thus, detect and isolate attackers on the fly. Comparative numerical simulation results support the validity of the approach.

2018 Oriental COCOSDA - International Conference on Speech Database and Assessments, 2018

In this paper, we present an account of an ongoing effort in creation of speech corpora of under-... more In this paper, we present an account of an ongoing effort in creation of speech corpora of under-resourced languages of North-East India, namely, Assamese, Bengali and Nepali. The speech corpora are being created for development of Automatic Speech Recognition system in Assamese as well as for Language Identification system. The text corpus of Assamese language comprises of 1000 sentences collected from different sources such as story books, novels, proverbs. Speech data are recorded over telephone channel using an interactive voice response system. Speakers were asked to read one or more sets of sentences, each set containing 20 sentences. Speech was simultaneously recorded using a hand-held audio recorder. While significant amount of speech data has been collected for Assamese language, the task has begun for Bengali, Nepali and English spoken by native speakers of these 3 languages. Currently, the Assamese speech database contains more than 5000 utterances by 27 native speakers. ...

The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages

The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages

2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2015

The primary objective of speech signal is the transfer of linguistic message. However, the acoust... more The primary objective of speech signal is the transfer of linguistic message. However, the acoustic signal also contains auxiliary information related to language, speaker, acoustic environment etc. Automatic recognition of the language of speech signal is not only scientifically interesting but also of technological importance in a multilingual country such as India. While a few language identification systems in the context of Indian languages have been implemented, most such systems have used small scale speech data collected internally within the organization. Recently, the Babel program of IARPA has released challenging speech data in three Indian languages: Assamese, Bengali and Tamil. Here, we report the development of an automatic language identification (LID) system that recognises the language of a given speech signal in any of these 3 languages. The LID system is built as an layer over the Automatic Speech Recognition (ASR) systems of these 3 languages trained using the B...

IEEE Systems Journal, 2018

Collaborative sensing helps in achieving a more accurate sensing decision than individual sensing... more Collaborative sensing helps in achieving a more accurate sensing decision than individual sensing in cognitive radio network (CRN). In an infrastructure-based CRN, each node sends its local sensing report to the fusion center (FC), which uses a fusion rule to aggregate the local sensing reports. However, collaborative sensing is vulnerable to the spectrum sensing data falsification attack, in which a node falsifies its local sensing report before sending it to the FC with the intention of disrupting the final sensing decision of the FC. In practice, the strategy of an attacker is not known. However, the collection of sensing reports at the FC can be useful for data mining with the objective of identifying the attackers. In this paper, we present a method that uses clustering techniques for detection and isolation of such attackers. We employ two clustering techniques, viz., K-medoids clustering and agglomerative hierarchical clustering. Unlike threshold detection that requires some predefined threshold value as input, the proposed approach detects the attackers using only the collection of sensing reports at the FC. We also present how we can use the proposed approach on streaming data (sensing reports), and thus, detect and isolate attackers on the fly. Comparative numerical simulation results support the validity of the approach.

2018 Oriental COCOSDA - International Conference on Speech Database and Assessments, 2018

In this paper, we present an account of an ongoing effort in creation of speech corpora of under-... more In this paper, we present an account of an ongoing effort in creation of speech corpora of under-resourced languages of North-East India, namely, Assamese, Bengali and Nepali. The speech corpora are being created for development of Automatic Speech Recognition system in Assamese as well as for Language Identification system. The text corpus of Assamese language comprises of 1000 sentences collected from different sources such as story books, novels, proverbs. Speech data are recorded over telephone channel using an interactive voice response system. Speakers were asked to read one or more sets of sentences, each set containing 20 sentences. Speech was simultaneously recorded using a hand-held audio recorder. While significant amount of speech data has been collected for Assamese language, the task has begun for Bengali, Nepali and English spoken by native speakers of these 3 languages. Currently, the Assamese speech database contains more than 5000 utterances by 27 native speakers. ...

The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages

The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages

2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2015