| dbo:abstract |
An acoustic model is used in automatic speech recognition to represent the relationship between an audio signal and the phonemes or other linguistic units that make up speech. The model is learned from a set of audio recordings and their corresponding transcripts. It is created by taking audio recordings of speech, and their text transcriptions, and using software to create statistical representations of the sounds that make up each word. (en) 声学模型（Acoustic model）是语音识别系统中最为重要的部分之一，目前的主流系统多采用隐马尔科夫模型进行建模。隐马尔可夫模型的概念是一个离散时域有限状态自动机，隐马尔可夫模型HMM是指这一马尔可夫模型的内部状态外界不可见，外界只能看到各个时刻的输出值。对语音识别系统，输出值通常就是从各个帧计算而得的声学特征。用HMM刻画语音信号需作出两个假设，一是内部状态的转移只与上一状态有关，另一是输出值只与当前状态（或当前的状态转移）有关，这两个假设大大降低了模型的复杂度。HMM的打分、解码和训练相应的算法是前向算法、维特比算法和前向后向算法。 (zh) |
| dbo:wikiPageExternalLink |
http://julius.sourceforge.jp/en_index.php%3Fq=en/index.html%23about_models http://www.keithv.com/software/htk/us/ http://www.repository.voxforge1.org/downloads/Nightly_Builds/ |
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dbr:Sampling_rate dbr:Julius_(software) dbr:VoxForge dbr:Automatic_speech_recognition dbr:Telephony dbr:Convolutional_neural_network dbr:Phonemes dbr:Speech dbr:HTK_(software) dbr:Language_model dbr:Audio_encoder dbc:Computational_linguistics dbc:Speech_recognition dbr:Codec dbr:Audio_signal dbr:Sound_card dbr:Mel-frequency_cepstrum dbr:Voice_over_IP |
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dbt:Refimprove dbt:Reflist |
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dbc:Computational_linguistics dbc:Speech_recognition |
| rdfs:comment |
An acoustic model is used in automatic speech recognition to represent the relationship between an audio signal and the phonemes or other linguistic units that make up speech. The model is learned from a set of audio recordings and their corresponding transcripts. It is created by taking audio recordings of speech, and their text transcriptions, and using software to create statistical representations of the sounds that make up each word. (en) 声学模型（Acoustic model）是语音识别系统中最为重要的部分之一，目前的主流系统多采用隐马尔科夫模型进行建模。隐马尔可夫模型的概念是一个离散时域有限状态自动机，隐马尔可夫模型HMM是指这一马尔可夫模型的内部状态外界不可见，外界只能看到各个时刻的输出值。对语音识别系统，输出值通常就是从各个帧计算而得的声学特征。用HMM刻画语音信号需作出两个假设，一是内部状态的转移只与上一状态有关，另一是输出值只与当前状态（或当前的状态转移）有关，这两个假设大大降低了模型的复杂度。HMM的打分、解码和训练相应的算法是前向算法、维特比算法和前向后向算法。 (zh) |
| rdfs:label |
Acoustic model (en) 声学模型 (zh) |
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freebase:Acoustic model wikidata:Acoustic model dbpedia-zh:Acoustic model https://global.dbpedia.org/id/4KtMq |
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wikipedia-en:Acoustic_model?oldid=934100482&ns=0 |
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