搜索资源列表
bibliofond_7397
- A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM toolbox for Matlab ... Speech recognition and segmentation. • Gesture .-A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM too
05947599
- 基于matlab对语音信号的分析，利用各种滤波器，频谱分析等功能。-Based on matlab analysis of speech signals, using various filters, spectral analysis and other functions.
Compress-Sensing_Apply_5Ref
- 压缩感知的5篇应用文献，包括CS在雷达成像、语音信号处理和图像处理方面的应用，新颖程度有一定参考价值。-5 compressed sensing references, including CS in radar imaging, speech signal processing and image processing applications, the novelty has some reference merits.
AMR-format
- Compressed audio format developed by Ericsson used by many 3G cell phones for voice recordings such as MMS messages incorporates the Algebraic Code Excited Linear Prediction (ACELP) algorithm, which is designed to efficiently compress human speech au
Baidu-World-2011-Cloud-Computing-.pdf
- 百度世界2011云计算论坛演讲稿：海量数据处理-Baidu World 2011 Cloud Computing Forum speech: massive data processing
dictionary
- important dictionary for simon speech recognizer in ptbr
micproject.zip
- Speech Processing Project,Speech Processing Project
hmm-tutorial
- The Hidden Markov Model (HMM) is a popular statistical tool for modelling a wide range of time series data. In the context of natural language processing(NLP), HMMs have been applied with great success to problems such as part-of-speech tagging a
hmm_paper_rabiner
- A tutorial an hidden markov models and selected applications in speech recognition
3
- Implementation of speech compression using Wavelet Transform
HMM
- HMM识别孤立词的研究与实现,有助于学习语音识别-HMM isolated word recognition and implementation of research, contribute to learning speech recognition
Audio_Speech_and_Language_Pr
- research paper on audio speech proccessing
yuyingshibie
- 基于SOPC的语音识别系统 语音分帧、加窗及端点检测部分程序细节-The speech recognition system based on SOPC Speech frame, window and endpoint detection part program details
tain
- 耳蜗实质上相当于一个滤波器组，耳蜗的滤波作用是在对数频率尺度上进行的，在1000HZ下，人耳的感知能力与频率成线性关系；而在1000HZ以上，人耳的感知能力与频率不构成线性关系，而更偏向于对数关系，这就使得人耳对低频信号比高频信号更敏感。Mel频率的提出是为了方便人耳对不同频率语音的感知特性的研究。频率与Mel频率的转换公式为-Cochlear substantially equivalent to a filter set, cochlear filter is used on logarit
ondelette
- Signal processing front end for extracting the feature set is an important stage in any speech recognition system. The optimum feature set is still not yet decided. There are many types of features, which are derived differently and have good
_18F26K22_Test_DS1307
- Describe: Speech signal feature extraction and analysis
31296_IEEE_PDF_Spec
- Describe: Speech signal feature extraction and analysis
CARTE_I2C_ET_LCD_1
- Describe: Speech signal feature extraction and analysis
Keypad
- Describe: Speech signal feature extraction and analysis
noisex-92
- Noise-92 can be used for speech enhancement experiment, including babble, pink noises etc. -Noise-92 can be used for speech enhancement experiment, including babble, pink noises etc.