• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2240-2243
• /
• 2003

In this paper. we present a new speech recognition system using DSP chip. DSP chip used TMS320c6711 of TI. We designed hardware system including acoustic model, word list and code book in flash memory. The word candidates are recognized based on CV, VCCV, and VC units HMM. This system can be applied to various electric ＆ electronic devices: home automation, robotics etc.

• Speech Sciences
• /
• v.15 no.1
• /
• pp.75-83
• /
• 2008

The interior of an automobile is a very noisy environment with both stationary cruising noise and the reverberated music or speech coming out from the audio system. For robust speech recognition in a car environment, it is necessary to extract a driver's voice command well by removing those background noises. Since we can handle the music and speech signals from an audio system in a car, the reverberated music and speech sounds can be removed using an acoustic echo canceller. In this paper, we implement an acoustic echo canceller with robust double-talk detection algorithm using TMS-320C6711 DSK. First we developed the echo canceller on the PC for verifying the performance of echo cancellation, then implemented it on the TMS320C6711 DSK. For processing of one speech sample with 8kHz sampling rate and 256 filter taps of the echo canceller, the implemented system used only 0.035ms and achieved the ERLE of 20.73dB.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.2C
• /
• pp.291-297
• /
• 2004

In this paper, a new structure for the AEC(Acoustic Echo Canceller) is proposed in which echo signal components that can be created in mobile communications is effectively eliminated. Block Data Flow Architecture is a parallel architecture that achieves high performance, high efficiency, high throughput, and almost linear speed up. The proposed architecture employs AEC and is implemented using the TMS320C6711 for real-time applications. The proposed AEC shows improved performance by eliminating echoes at 55ms delay path. Since the proposed AEC can also be implemented in Firmware, it is believed to effectively work on various types of echoes if it is applied on CDMA mobile devices. The TMS320C6711 shows much better performance comparing to previous DSPs. For experimental verifications, filtering operation using adaptive algorithm is performed on TMS320C6711 board and error signals resulted from computations are monitored on PC, and then the performance of the implemented AEC is verified through ERLE computation. According the results of simulation, good characteristic of 100dB are shown after 500 sampling data.

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.391-394
• /
• 2004

This paper focuses on the DSP implementation of an HMM-based speech recognizer that can handle several hundred words of vocabulary size as well as speaker independency. First, we develop an HMM-based speech recognition system on the PC that operates on the frame basis with parallel processing of feature extraction and Viterbi decoding to make the processing delay as small as possible. Many techniques such as linear discriminant analysis, state-based Gaussian selection, and phonetic tied mixture model are employed for reduction of computational burden and memory size. The system is then properly optimized and compiled on the TMS320C6711 DSP for real-time operation. The implemented system uses 486kbytes of memory for data and acoustic models, and 24.5kbytes for program code. Maximum required time of 29.2ms for processing a frame of 32ms of speech validates real-time operation of the implemented system.

• MALSORI
• /
• no.52
• /
• pp.111-120
• /
• 2004

This paper focuses on the DSP implementation of an HMM-based speech recognizer that can handle several hundred words of vocabulary size as well as speaker independency. First, we develop an HMM-based speech recognition system on the PC that operates on the frame basis with parallel processing of feature extraction and Viterbi decoding to make the processing delay as small as possible. Many techniques such as linear discriminant analysis, state-based Gaussian selection, and phonetic tied mixture model are employed for reduction of computational burden and memory size. The system is then properly optimized and compiled on the TMS320C6711 DSP for real-time operation. The implemented system uses 486kbytes of memory for data and acoustic models, and 24.5 kbytes for program code. Maximum required time of 29.2 ms for processing a frame of 32 ms of speech validates real-time operation of the implemented system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.18 no.1
• /
• pp.129-136
• /
• 2004

In this paper, we proposed quad variable rates ADPCM coding method for efficient speech transmission and real time porcessing is implemented on TMS320C6711-DSP. The modified ADPCM with four variable coding rates, 16[kbps], 24[kbps], 32[kbps] and 40[kbps] are used for speech window samples for good quality speech transmission at a small data bits and real time encoding and decoding is implemented using DSP. ZCR is used to identify the influence of the noise on the speech signal and to decide the rate change threshold. For noise superior signals, low coding rates are applied to minimize data bit and for noise inferior signals, high coding rates are applied to enhance the speech quality. In most speech telecommunications, silent period takes more than half of the signals, speech quality close to 40[kbps] can be obtained at comparabley low data bits and this is shown by simulation and experiments. TMS320C6711-DSK board has 128K flash memory and performance of 1333MIPS and has meets the requirements for real time implementation of proposed coding algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.1E
• /
• pp.20-24
• /
• 2006

In this paper, we focused on the real time implementation of a speech recognition system with medium size of vocabulary considering its application to a mobile phone. First, we developed the PC based variable vocabulary word recognizer having the size of program memory and total acoustic models as small as possible. To reduce the memory size of acoustic models, linear discriminant analysis and phonetic tied mixture were applied in the feature selection process and training HMMs, respectively. In addition, state based Gaussian selection method with the real time cepstral normalization was used for reduction of computational load and robust recognition. Then, we verified the real-time operation of the implemented recognition system on the TMS320C6201 EVM board. The implemented recognition system uses memory size of about 610 kbytes including both program memory and data memory. The recognition rate was 95.86% for ETRI 445DB, and 96.4%, 97.92%, 87.04% for three kinds of name databases collected through the mobile phones.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.1
• /
• pp.48-52
• /
• 2005

In this paper, the spectral shape invariant real-time voice change method is proposed to change one's voice to mechanical voice. For this purpose, LPC analysis and synthesis is used to maintain the spectraum of voice and the pitch of synthesis speech can be changed freely. In the proposed method, gain matching method is applied to excitation signal generator to make the changed voice natural to hear. In order to evaluate the performance of the proposed method, voice change experiments were conducted. Experimental results showed that original speech signal is changed to the mechanical voice signal in which context of the speaker's voice is conveyed correctly in spite of drastic change of pitch. The system is implemented using TI TMS320C6711DSK board to verify the system runs in real time.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.759-763
• /
• 2004

In this paper, real-time voice change method using pitch change technique is proposed to change one's voice to the other voice. For this purpose, sampling rate change method using DFT (Discrete Fourier Transform) method and time scale modification method using SOLA (Synchronized Overlap and Add) method is combined to change pitch. In order to evaluate the performance of the proposed method, voice transformation experiments were conducted. Experimental results showed that original speech signal is changed to the other speech signal in which original speaker's identity is difficult to find. The system is implemented using TI TMS320C6711DSK board to verify the system runs in real time.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.2
• /
• pp.366-373
• /
• 2007

In this paper we propose a multi-channel speech pickup system for calling quality enhancement of hands-free communication using ALTERA Nios-II processor. Multi-channel speech pickup system uses Delay-and-Sum beamformer with zero-padding interpolator. This paper implements speech pickup system using the Nios-II processor with real-time I/O data processing speed. The proposes speech pickup embedded system shows a good agreement with those of computer simulation(MATLAB) and conventional DSP processor(TMS320C6711) result. The proposed method is effective more than previous methods in cost and design processing time. As a result, LE(Logic Element) of hardware used 3,649/5,980(61%) on a chip.