Major Challenges of Voice Command Recognition Technique

Human listeners are capable of identifying a speaker, over the telephone or an entryway out of sight, by listening to the voice of the speaker. Achieving this intrinsic human specific capability is a major challenge for Voice Biometrics. Like human listeners, voice biometrics uses the features of a person's voice to ascertain the speaker's identity. The best-known commercialized form of voice biometrics is Speech Recognition System (SRS). Speech recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voice. This paper gives a brief introduction of SRS describing how the technology works, and then discusses the general architecture of SRS, methodologies, merits of using this system, major technological perspective and appreciation of the fundamental progress of speech recognition. It gives an approach to the recognition of speech signal using frequency spectral information with Mel frequency for the improvement of speech feature representation in a HMM based recognition approach and also gives overview of techniques developed in each stage of speech recognition along with the current and future researches on the same. This paper describes the major challenges for SRS system which have been came across by users feedback and various researches which has to be resolved as soon as possible for better performance outcome. Index Terms— SRS (Speech recognition system), ASR (automatic speech recognition), MFCC (Mel frequency cepstral coefficient), DTW (dynamic time wrap), HMM (hidden markov models), WER (word error rate), WRR (word recognition rate). ——————————  ——————————