Raziel Haimi-Cohen

High-accuracy connected digit recognition for mobile applications

We present a connected digit recognition system with low storage and computational complexity which achieves good performance in car noise. Our system uses the TI-DIGITS database with additive car noise for training whole-word digit and background models. A digit accuracy of 96.1% is obtained on a 15-speaker database collected in a car using an open microphone with an average SNR of approximately 2 dB. There is a further error reduction of almost 35% if the top two candidate strings are considered using a traceback based N-best algorithm. The system can be implemented on a currently available fixed-point DSP chip. We show that significant performance improvements are obtained by using two-level cepstral mean subtraction (CMS), gender-dependent models and a decoding grammar constraining the possible lengths of digit strings.

Quantizing mixture-weights in a tied-mixture HMM

We describe new techniques to significantly reduce computational, storage and memory access requirements of a tied mixture HMM based speech recognition system. Although continuous mixture HMMs offer improved recognition performance, we show that tied mixture HMMs may offer significant advantage in complexity reduction for low cost implementations. In particular, we consider two tasks: (a) connected digit recognition in car noise; and (b) subword modeling for command word recognition in a noisy office environment. We show that quantization of mixture weights can provide an almost three fold reduction in mixture weight storage requirements without any significant loss in recognition performance. Furthermore, we show that by combining mixture weight quantization with techniques such as VQ-Assist, the computational and memory access requirements can be reduced by almost 60-80% without any degradation in recognition performance.

DSPs in mobile communication in the United States

The mobile communication industry in the United States is undergoing major changes. Auctioning of additional spectrum will lead to more service providers and will significantly increase competition. Service providers are likely to customize the services they offer to differentiate themselves from others. We discuss possible technologies for differentiation of services and the implications of these on the requirements for embedded digital signal processors (DSPs). In the US, supporting at least three widely used air interfaces will be a challenge to the industry. The need for customization in the context of multiple standards will create strong pressure to significantly improve the firmware development environment for DSPs. This also implies evolution to architectures that are more friendly to developers.