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One of the major reasons for the performance degradation of a speaker verification (SV) system in real-world conditions is its inability to spot speech regions due to the presence of noise. This work focuses on the role of voice activity detection (VAD) methods in alleviating such shortcomings. The experiments are conducted on the core-core task of the speakers in the wild (SITW) challenge. Two VAD...
In this paper, the speech signal recorded from the desired speaker close to microphone in natural environment is regarded as foreground speech and rest of the interfering sources as background noise . The proposed paper exploits speech production features like glottal closure instants in time domain and vocal tract information in spectral domain to segment the desired speaker's speech and to further...
The signal characteristics of speech collected over microphone depends on the distance between the speaker and sensor, and also on the presence of other background acoustic sources. In the present work, if the microphone is kept close to the speaker, then it is termed as Foreground scenario, otherwise Distant scenario. Even though, presence of other background acoustic sources affect the signal characteristics...
The speaker change information in speech is due to both vocal tract and excitation source information. In this work, the excitation source information is extracted by computing cepstral features from the zero frequency filtered speech (ZFFS) signal. The vocal tract system information is extracted by computing cepstral features from the speech signal. The speaker change evidences obtained from these...
In this work, speech signal having information up to 4 kHz is termed as narrowband (NB) speech and the other having information up to 8 kHz is termed as wideband (WB) speech. The objective is to demonstrate the significance of speaker information present in the WB speech. A speaker verification (SV) system is developed using the mel-frequency cepstral coefficients (MFCCs) computed from the WB speech...
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