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Multi-domain language recognition involves the application of a language identification (LID) system to identify languages in more than one domain. This problem was the focus of the recent NIST LRE 2017, and this article presents the findings from the SRI team during system development for the...

Jun, 2018
Conference Paper
Topics:
420

With the recent introduction of speaker embeddings for text-independent speaker recognition, many fundamental questions require addressing in order to fast-track the development of this new era of technology. Of particular interest is the ability of the speaker embeddings network to leverage...

Jun, 2018
Conference Paper
Topics:
420

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
420

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
420

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
420

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
420
By Vikramjit Mitra

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

May, 2017
Journal
420

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:
420

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

Sep, 2016
Technical Report
420
By Vikramjit Mitra, Dimitra Vergyri, Horacio Franco

Often, prior knowledge of subword units is unavailable for low-resource languages. Instead, a global subword unit description, such as a universal phone set, is typically used in such scenarios.

Sep, 2016
In Proceedings
Topics:
420

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