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While acoustic-based links between clinical depression and abnormal speech have been established, there is still however little knowledge regarding what kinds of phonological content is most impacted.

Oct, 2017
Conference Paper
418

To date, automatic spoken language detection research has largely been based on a closed-set paradigm, in which the languages to be detected are known prior to system application. In actual practice, such systems may face previously unseen languages (out-of-set (OOS) languages) which should be...

Aug, 2017
In Proceedings
418

Unsupervised techniques for the adaptation of speaker recognition are important due to the problem of condition mismatch that is prevalent when applying speaker recognition technology to new conditions and the general scarcity of labeled ‘in-domain’ data.

Aug, 2017
In Proceedings
418

Speech conveys many things beyond content, including aspects of stance and attitude that have not been much studied. Considering 14 aspects of stance as they occur in radio news stories, we investigated the extent to which they could be inferred from prosody

Aug, 2017
In Proceedings
418
By Vikramjit Mitra

Studies have shown that articulatory information helps model speech variability and, consequently, improves speech recognition performance.

May, 2017
Journal
418

This work addresses lexical unit discovery for languages without (usable) written resources. Previous work has addressed this problem using entirely unsupervised methodologies. Our approach in contrast investigates the use of linguistic and speaker knowledge which are often available even if text...

Mar, 2017
Conference Paper
Topics:
418

The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8...

Sep, 2016
In Proceedings
Topics:
418

This article is concerned with the issue of calibration in the context of Deep Neural Network (DNN) based approaches to speaker recognition. DNNs have provided a new standard in technology when used in place of the traditional universal background model (UBM) for feature alignment, or to augment...

Sep, 2016
In Proceedings
Topics:
418
By Vikramjit Mitra, Horacio Franco

The introduction of deep neural networks has significantly improved automatic speech recognition performance.

Sep, 2016
In Proceedings
Topics:
418

This work investigates whether nonlexical information from speech can automatically predict the quality of small-group collaborations.

Sep, 2016
Technical Report
418

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