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MirasVoice: A bilingual (English-Persian) speech corpus

Speech and speaker recognition is one of the most important research and development areas and has received quite a lot of attention in recent years. The desire to produce a natural form of communication between humans and machines can be considered the motivating factor behind such developments. Speech has the potential to influence numerous fields of research and development. In this paper, MirasVoice which is a bilingual (English-Farsi) speech corpus is presented. Over 50 native Iranian speakers who were able to speak in both the Farsi and English languages have volunteered to help create this bilingual corpus. The volunteers read text documents and then had to answer questions spontaneously in both English and Farsi. The text-independent GMM-UBM speaker verification engine was designed in this study for validating and exploring the performance of this corpus. This multilingual speech corpus could be used in a variety of language dependent and independent applications. For example, it can be used to investigate the effects of different languages (Farsi and English) on the performance of speaker verification systems. The authors of this paper have also investigated speaker verification systems performances when using different train/test architectures.