A review on speaker recognition: Technology and challenges


Fig. 2. Framework of a speaker identification system. Table 3



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Fig. 2. Framework of a speaker identification system.
Table 3
Comparison of different feature extraction techniques.

Technique

Merits

De-merits

LPC

  • Based on basic principles of sound production [20].

  • Simple to implement and mathematically precise [19].

  • Performance degradation in the presence of noise [20, 23].

  • It does not represent vocal tract characteristics from the glottal dynamic; thus, consumes time and computational cost [9].

  • Inconsistency with human hearing [24].

LPCC

  • Smoother spectral envelope and stable representation as compared with LPC [20].

  • Feature components are decorrelated [19, 25].

  • Linearly spaced frequency bands, which is inadequate [19,25].

  • Sensitive to the quantization noise [23].

  • The performance is degraded in case of using insufficient order [23].

MFCC

  • More information on lower frequencies than higher frequencies due to mel-spaced filter banks. Hence, behaves like human ear compared with other techniques [20, 26].

  • Captures the main characteristics of phones in speeches with low complexity [27].

  • Based on Short-Time Fourier Transform (STFT) which has fixed time-frequency resolution [26].

  • Low robustness to noise [19, 28].




      1. Authentication

Authentication is one of the most popular biometric applications as it allows the users to identify an individual based on his/her voice. Usually, to authenticate the speaker, a combination of techniques is used, such as a password or facial recognition [22]. This biometric authentication could reduce the problems of misused identity and is also more convenient than using a Personal Identifi­cation Number (PIN) or password, which can be easily forgotten. In 2015, Gomar invented and patented a speaker recognition system for authenticating a mobile device user [29]. The system produced a biometric voiceprint from the user’s speech utterances which are stored in the mobile device when it met a quality threshold. For verification purposes, the user will need to utter an attribute from the biometric voiceprint in order to be an authorized user.

      1. Personalization

A personal digital assistant used to be a luxury reserved for the wealthy, but it is no longer the case nowadays as everyone can have a digital assistant. Siri, Alexa, Cortana, and Google Now, to name just a few, are examples of software that can help us comprehend and carry out our capricious spoken commands. We can do anything with them, such as planning for meetings, event scheduling, shopping,


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