Speaker recognition in noisy environments using auxiliary information and Bayesian networks
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Speaker diarization is the task of identifying ``who spoke when'' in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization sys ...
Automatic processing of multiparty interactions is a research domain with important applications in content browsing, summarization and information retrieval. In recent years, several works have been devoted to find regular patterns which speakers exhibit ...
This paper presents Subspace Gaussian Mixture Model (SGMM) approach employed as a probabilistic generative model to estimate speaker vector representations to be subsequently used in the speaker verification task. SGMMs have already been shown to significa ...
This paper presents Subspace Gaussian Mixture Model (SGMM) approach employed as a probabilistic generative model to estimate speaker vector representations to be subsequently used in the speaker verification task. SGMMs have already been shown to significa ...
This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically inv ...
Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR- based adaptation te ...
This paper investigates employment of Subspace Gaussian Mixture Models (SGMMs) for acoustic model adaptation towards different accents for English speech recognition. The SGMMs comprise globally-shared and state-specific parameters which can efficiently be ...
Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR based adaptation tec ...
This paper investigates employment of Subspace Gaussian Mixture Models (SGMMs) for acoustic model adaptation towards different accents for English speech recognition. The SGMMs comprise globally-shared and state-specific parameters which can efficiently be ...
This paper demonstrates the robustness of group-delay based features for speech processing. An analysis of group delay functions is presented which show that these features retain formant structure even in noise. Furthermore, a speaker verification task pe ...
