Approximately, seven years before speech recognition was not as lucrative as it looks today. Error ratio was so high that the developers were reluctant to launch an application with speech recognition for the public. But thanks to some of the robust digital signal processing techniques which were instrumental to increasing the rate of accuracy. As on date, speech recognition is available elsewhere and especially in Google search. It is also playing a key role in automotive telematics, mobile phone technology, conferencing system and similar telecom applications. Over the years, speech recognition has been optimized with DSP technology and in turn has improved the rate of accuracy in speech recognition.
Overcoming Noise from the Background & Noise Reduction
The best possible solution to increase rate of accuracy in speech recognition is to avoid background noise. Initially, each short segment of speech is analyzed and its important characteristics are placed into a feature vector. So when each short segment of speech is analyzed, it counts the basic sound of each letter. For example, if you pronounce cat, it breaks down the letters as K A T. Analyzing the sound of the word C. If there is noise in between, there might be a mispronunciation which will lead to inaccuracy. Digital signal processing uses reconstruction filters to overcome background noise and noise reduction.
Control of Accuracy
The same sophisticated reconstruction filters you read above are the reasons why DSP could offer high accuracy in speech recognition. Tolerance of circuit components in analog filters is the reason why it has high amount of noise. Also, in case of reconfiguring analog system will mean complete redesigning of system hardware. But with DSP, configuring takes place with ease and there is no tolerance of circuit components like in analog filters. Hence digital signal processing offers impeccable control of accuracy for speech recognition.
Easy Implementation of Sophisticated Signal Processing
Implementing sophisticated signal processing becomes much simpler with DSP. In analog processing, there is no big scope of using sophisticated signal processing due to its non-dynamic nature. Integrating it with sophisticated processing applications took a lot of time. But whereas with DSP, integration and implementation of these entire sophisticated signal processing becomes quite easier. For example, implementation of wireless systems with DSP involves integration with FPGA. Using these entire wireless systems like WiMAX, LTE etc. can be setup without any hassles and in a very short time.
The best of all reasons to have DSP for speech recognition is cost effectiveness. Compared to analog, the environment required to setup digital is relatively less expensive and involves low cost. Hence in all ways it is quite viable and especially to simplify and improve accuracy in speech recognition, DSP is very much required.
Technosoft Innovations with an experience of two decades in the field of digital signal processing offers impeccable solutions to simplify complex processes. Refer to this page to understand how the offerings of Technosoft are unique and how it keeps your ante up in the market. Also know some of the Digital Signal Processing Applications.