Speaker Recognition and Speaker Characterization over Landline, VoIP and Wireless Channels

The automatic detection of people's identity and characteristics such as age, gender, emotion and personality from their voices generally requires the transmission of the speech to remote servers that perform the recognition task. This transmission may introduce severe distortions and channel mismatch that degrade the system performance or vary the detection of the actual emotions and speaker traits. Concurrently, humans also cope with the difficulty of reliably identifying and characterizing talkers from speech transmitted over telephone channels, particularly detecting emotions on a call to a friend or relative. The present research addresses the evaluation of human and automatic performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Special attention is paid to the creation of robust automatic systems that can handle channel variations, and thus enhance voice-based human-computer interaction in applications where the speech is transmitted. This paper outlines the work completed to date and the potential future work plans to be finalized within the next 1.5 years.