System and method to correct for packet loss using hidden markov models in ASR systems
OwnerSrinath Cheluvaraja, Ananth Nagaraja Iyer +2inventors
InventorsSrinath Cheluvaraja, Ananth Nagaraja Iyer, Aravind Ganapathiraju, Felix Immanuel Wyss
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Abstract
A system and method are presented for the correction of packet loss in audio in automatic speech recognition (ASR) systems. Packet loss correction, as presented herein, occurs at the recognition stage without modifying any of the acoustic models generated during training. The behavior of the ASR engine in the absence of packet loss is thus not altered. To accomplish this, the actual input signal may be rectified, the recognition scores may be normalized to account for signal errors, and a best-estimate method using information from previous frames and acoustic models may be used to replace the noisy signal.
Claims6
A method to correct for packet loss in an audio signal in automatic speech recognition systems comprising maximum likelihood prediction wherein the maximum likelihood prediction further comprises the steps of:
- a. determining Hidden Markov Model state occupation probabilities in an acoustic model within the automatic speech recognition system prior to a packet loss event, wherein the Hidden Markov Model state occupation probabilities are determined using the mathematical equation
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- where P represents a probability distribution of a feature vector at x(t+1), alpha(i) represents a state occupation probability at time t for state (i), t(ik) represents a state transition probability from state i to k, and where b(k)(x(t+1)) represents a Gaussian mixture distribution for a feature x(t+1) from a state k belonging to a phoneme model;
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- b. predicting feature values of packets in the packet loss section of the audio signal based on the determined Hidden Markov Model state occupation probabilities.
Dependencies are inferred from the claim text.