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AbstractThe endpoint detection of speech signal is the basic link of digital speech signal processing. However, speech signals make the endpoints fuzzy due to the presence of various noises, including voiceless segments, clear segments and turbid segments, which bring great difficulties to endpoint detection. In this paper, to address this problem, combined with the characteristics of the actual speech signal, the algorithm of double threshold combining short-time energy and over-zero rate is adopted to realize the endpoint detection of a given speech file. The article firstly analyzes the characteristics of short-time energy and over-zero rate in detail; on this basis, combined with the powerful computing tool MATLAB, the program of double threshold algorithm is written to realize the end-point detection of the speech signal; finally, the GUI of MATLAB is used to create the operation interface of the end-point detection of the speech signal, which is convenient for the realization of the end-point detection of the speech signal.
Theabstractpronunciationsignalvertexexaminationisthedigitalpronunciationsignalprocessingfoundationlink. Butpronunciationsignalbecausehaseachkindofstatic,includingthesilentsection,thevoicelesssoundsectionandthevoicedsoundsectionandsoon ,causesthevertexquitetobefuzzy,hasbroughttheverymajordifficultyforthevertexexamination.Thisarticleinviewofthisquestion, the theunionactualpronunciationsignalcharacteristic,hasusedtheshort- timeenergyandthedoublethresholdalgorithmwhichzerorateunifieshasrealizedtoassignsthepronunciationdocumentthevertexexamination. Articlefirstmultianalysisshort-timeenergyandzeroratecharacteristic;Inthisfoundation, the unifiedformidablecomputationtoolMATLABtocompilethedoublethresholdalgorithmprocere, hasrealizedtothepronunciationdocumentationthevertexamination. hasrealizedtothepronunciationsignalvertexexamination. FinallyhasmanufacturedthepronunciationsignalvertexexaminationoperationcontactsurfaceusingMATLABgraphicaluserinterfaceGUI, facilitatestothepronunciationsignalvertexamination. facilitateatestothepronunciationsignalrealizationvertexexamination.
This thesis mainly introduces the research background of this topic, the characteristics of speech, speech endpoint detection methods, speech endpoint detection algorithms based on MATLAB.
Keywordsendpointdetection;short -timeenergy;cross-zero rate;MATLAB
Dubbing software how to develop
Comprehensive speech recognition technology, speech synthesis technology, graphical interface design and software development technology can be developed in four areas.
1, speech recognition technology: dubbing software needs to be able to recognize what the user is talking about and convert it into text or instructions, so you need to use speech recognition technology, including acoustic models, language models, speech signal processing.
2, speech synthesis technology: dubbing software needs to be able to convert text into speech, and realize the adjustment of timbre, pitch, speech rate, etc., so it needs to use speech synthesis technology, including text analysis, pronunciation rules, acoustic parameters, etc..
3, graphical interface design: dubbing software needs to have a friendly interface, user-friendly, so the need for graphical interface design, including interface layout, button design, color scheme and so on.
4, software development technology: the development of dubbing software needs to use software development technology, including programming languages, development tools, data structures, algorithms and so on.
Which is better, voice signal processing or image signal processing
Voice signal processing
Digital signal processing
Of course, the image is better
The United States has completed the development of a standard for digital high-definition television, known as GA, and its timetable for entry into the field, while Europe is developing a stand-alone digital television program and has developed a standard for digital television broadcasting, DVB. All of this is based on the maturation of a range of technologies and standards for digital television source coding. Source coding, as a core component of a digital TV system, directly determines the basic format of digital TV and its signal coding efficiency, and determines how digital TV is ultimately realized in the actual system.
I. Source coding for digital TV
A complete digital TV system includes many aspects of digital TV signal generation, processing, transmission, reception and reproduction. The processing of digital TV signals before entering the transmission channel is generally shown in Figure 1:
The first processing link that a TV signal undergoes after acquisition is source coding. Source coding is through compression coding to remove redundant components of the signal source to achieve compression of bit rate and bandwidth, to achieve the purpose of effective signal transmission. Channel coding is to prevent errors in the transmission process by rearranging the signal elements according to certain rules or adding auxiliary codes, and to carry out error checking and error correction to ensure reliable transmission of the signal. The baseband signal after channel coding is modulated and can be fed into various types of channels for transmission. At present, the possible transmission channels of digital TV include satellite, terrestrial wireless transmission and cable transmission.
Low-cost FPGAs for video and image processing
FPGAs have been around for more than a decade, and in the traditional concept, FPGAs are expensive, with a high design threshold, and are mostly used in communications and high-end industrial control. In recent years, low-cost FPGAs have been pushing the envelope. Advances in semiconductor processes not only bring about a reduction in the cost of FPGAs, but also significantly improve their performance, while constantly integrating a number of new hardware resources, such as embedded DSP blocks, embedded RAM blocks, phase-locked loop (PLL), high-speed external memory interfaces (DDR/DDR2), high-speed LVDS interfaces and so on. Inside ALTERA’s 90nm CycloneII FPGA, a soft processor, NiosII, and its peripherals can also be integrated, which is currently the most widely used soft processor system in FPGAs.
As a platform, the FPGA has clearly been well suited for high-performance, low-cost video and imaging applications. It can help users flexibly customize their systems, shorten the cycle of product development and replacement, and enable them to keep up with technology and market development trends. This paper will first review the application areas of video and image processing, video processing flows, trends, and the challenges that designers must address. Then, a brief introduction to the resources and algorithm implementations within FPGAs will be given. Subsequently, the paper will describe the solutions offered to users by Altera and its partners in the video image application area. Finally, tools and flows for designing video image processing systems are given.
Technology and Challenges
Video and image processing technology is used in a wide range of applications, including digital television broadcasting, consumer electronics, automotive electronics, video surveillance, medical imaging, and document image processing. A typical video processing system includes: video acquisition, pre-processing, compression, signal transmission and reception, decompression, post-processing, and finally to the display control section, drive the display device. In all the constituent modules of the video processing system, there are FPGA successful application cases.
Video and image processing technology can be described as rapidly changing, researchers for video images and the human eye sensory research has never stopped, the new needs continue to give rise to technological innovation and new standards, mainly in the following areas: from standard definition (SD) to high-definition (HD), the resolution is getting higher and higher, and need to be more and more real-time processing of the amount of data; video and image compression technology is becoming more and more complex. Such as MPEG-4 Part 2, H.264AVC, JPEG2000, etc.; the video system intelligence requirements to improve, such as intelligent shooting, motion detection, object recognition, multi-channel, picture-in-picture, transparent superimposed effects, etc.; consumer appreciation of the ability to improve the hope that the image is more stable, clearer, more colorful, more brightness in line with the human eye’s sensory needs.
While the technical difficulties continue to increase, the cost and time-to-market are still two key considerations in the design of video and image application systems. At the same time, product differentiation and proprietary intellectual property rights are goals that some thoughtful Chinese companies are pursuing.
If you simply use off-the-shelf dedicated video image processing chips (ASSPs), you simply can’t design products with your own intellectual property rights and differentiate your products. Moreover, it is difficult to use ASSP to be flexible, easy to upgrade, as well as keep up with the trend of technology development. Manufacturers to develop their own ASIC cycle and too long, the initial investment is too large, the risk is very high, can not guarantee the return on investment, but also can not maintain technological leadership.
At present, even the most powerful monolithic DSP processors cannot compress (H.264) HD video in real time. The cost of using DSP arrays is unacceptable, while multiple DSP processors will bring difficulties in system partitioning and debugging, increase system instability, and increase PCB costs. If you use a single FPGA, or FPGA plus DSP processor to work together, these difficulties can be solved.
In short, the use of FPGA technology can help users to ensure a reasonable cost under the premise of developing high-performance products. The use of FPGA can be flexibly upgraded, the user can meet the ever-changing market demand, so that their products quickly push the new, follow the industry development trend, to make their own characteristics, independent intellectual property rights of the product, and always keep the product differentiation and leadership.