Turbo-detected unequal protection audio and speech transceivers using serially concatenated convolutional codes, trellis coded modulation and space-time trellis coding

The MPEG-4 TwinVQ audio codec and the AMR-WB speech codec are investigated in the context of a jointly optimised turbo transceiver capable of providing unequal error protection. The transceiver advocated consists of serially concatenated Space-Time Trellis Coding (STTC), Trellis Coded Modulation (TCM) and two different-rate Non-Systematic Convolutional codes (NSCs) used for unequal error protection. A benchmarker scheme combining STTC and a single-class protection NSC is used for comparison with the proposed scheme. The audio and speech performance of both schemes is evaluated, when communicating over uncorrelated Rayleigh fading channels. An $E_b/N_0$ value of about 2.5 (3.5)~dB is required for near-unimpaired audio (speech) transmission, which is about 3.07 (4.2)~dB from the capacity of the system

Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems

A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept

Recognizing GSM Digital Speech

The Global System for Mobile (GSM) environment encompasses three main problems for automatic speech recognition (ASR) systems: noisy scenarios, source coding distortion, and transmission errors. The first one has already received much attention; however, source coding distortion and transmission errors must be explicitly addressed. In this paper, we propose an alternative front-end for speech recognition over GSM networks. This front-end is specially conceived to be effective against source coding distortion and transmission errors. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bitstream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant advantages. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion as a result of the encoding-decoding process. Second, when transmission errors occur, our front-end becomes more effective since it is not affected by errors in bits allocated to the excitation signal. We have considered the half and the full-rate standard codecs and compared the proposed front-end with the conventional approach in two ASR tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated channel conditions. Furthermore, the disparity increases as the network conditions worsen