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    • 3. 发明授权
    • Automatic language model update
    • 自动语言模型更新
    • US07756708B2
    • 2010-07-13
    • US11396770
    • 2006-04-03
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • G10L15/06G10L15/08G10L15/00G06F17/30
    • G10L15/065G10L15/06G10L15/063G10L15/187G10L15/26G10L2015/0635
    • A method for generating a speech recognition model includes accessing a baseline speech recognition model, obtaining information related to recent language usage from search queries, and modifying the speech recognition model to revise probabilities of a portion of a sound occurrence based on the information. The portion of a sound may include a word. Also, a method for generating a speech recognition model, includes receiving at a search engine from a remote device an audio recording and a transcript that substantially represents at least a portion of the audio recording, synchronizing the transcript with the audio recording, extracting one or more letters from the transcript and extracting the associated pronunciation of the one or more letters from the audio recording, and generating a dictionary entry in a pronunciation dictionary.
    • 一种用于产生语音识别模型的方法,包括:访问基准语音识别模型,从搜索查询获得与最近的语言使用相关的信息,以及修改语音识别模型,以基于该信息修改声音发生的一部分的概率。 声音的一部分可能包含一个字。 另外,一种用于生成语音识别模型的方法包括:从搜索引擎从远程设备接收基本上表示音频记录的至少一部分的音频记录和抄本,将录音与音频记录同步,提取一个或 从录音中提取更多的字母,并且从音频记录中提取一个或多个字母的相关联的发音,以及在发音词典中生成字典条目。
    • 4. 发明申请
    • Automatic Language Model Update
    • 自动语言模型更新
    • US20130006640A1
    • 2013-01-03
    • US13616468
    • 2012-09-14
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • G10L15/18
    • G10L15/065G10L15/06G10L15/063G10L15/187G10L15/26G10L2015/0635
    • A method for generating a speech recognition model includes accessing a baseline speech recognition model, obtaining information related to recent language usage from search queries, and modifying the speech recognition model to revise probabilities of a portion of a sound occurrence based on the information. The portion of a sound may include a word. Also, a method for generating a speech recognition model, includes receiving at a search engine from a remote device an audio recording and a transcript that substantially represents at least a portion of the audio recording, synchronizing the transcript with the audio recording, extracting one or more letters from the transcript and extracting the associated pronunciation of the one or more letters from the audio recording, and generating a dictionary entry in a pronunciation dictionary.
    • 一种用于产生语音识别模型的方法,包括:访问基准语音识别模型,从搜索查询获得与最近的语言使用相关的信息,以及修改语音识别模型,以基于该信息修改声音发生的一部分的概率。 声音的一部分可能包含一个字。 另外,一种用于生成语音识别模型的方法包括:从搜索引擎从远程设备接收基本上表示音频记录的至少一部分的音频记录和抄本,将录音与音频记录同步,提取一个或 从录音中提取更多的字母,并且从音频记录中提取一个或多个字母的相关联的发音,以及在发音词典中生成字典条目。
    • 5. 发明申请
    • Automatic Language Model Update
    • 自动语言模型更新
    • US20110213613A1
    • 2011-09-01
    • US12786102
    • 2010-05-24
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • Michael H. CohenShumeet BalujaPedro J. Moreno
    • G10L15/26G10L15/06G06K9/72
    • G10L15/065G10L15/06G10L15/063G10L15/187G10L15/26G10L2015/0635
    • A method for generating a speech recognition model includes accessing a baseline speech recognition model, obtaining information related to recent language usage from search queries, and modifying the speech recognition model to revise probabilities of a portion of a sound occurrence based on the information. The portion of a sound may include a word. Also, a method for generating a speech recognition model, includes receiving at a search engine from a remote device an audio recording and a transcript that substantially represents at least a portion of the audio recording, synchronizing the transcript with the audio recording, extracting one or more letters from the transcript and extracting the associated pronunciation of the one or more letters from the audio recording, and generating a dictionary entry in a pronunciation dictionary.
    • 一种用于产生语音识别模型的方法,包括:访问基准语音识别模型,从搜索查询获得与最近的语言使用相关的信息,以及修改语音识别模型,以基于该信息修改声音发生的一部分的概率。 声音的一部分可能包含一个字。 另外,一种用于生成语音识别模型的方法包括:从搜索引擎从远程设备接收基本上表示音频记录的至少一部分的音频记录和抄本,将录音与音频记录同步,提取一个或 从录音中提取更多的字母,并且从音频记录中提取一个或多个字母的相关联的发音,以及在发音词典中生成字典条目。
    • 7. 发明授权
    • Aligning a transcript to audio data
    • 将抄本与音频数据对齐
    • US08131545B1
    • 2012-03-06
    • US12238257
    • 2008-09-25
    • Pedro J. MorenoChristopher Alberti
    • Pedro J. MorenoChristopher Alberti
    • G10L15/26
    • G10L15/04
    • The subject matter of this specification can be implemented in, among other things, a computer-implemented method including receiving audio data and a transcript of the audio data. The method further includes generating a language model including a factor automaton that includes automaton states and arcs, each of the automaton arcs corresponding to a language element from the transcript. The method further includes receiving language elements recognized from the received audio data and times at which each of the recognized language elements occur in the audio data. The method further includes comparing the recognized language elements to one or more of the language elements from the factor automaton to identify times at which the one or more of the language elements from the transcript occur in the audio data. The method further includes aligning a portion of the transcript with a portion of the audio data using the identified times.
    • 除了别的以外,本说明书的主题可以实现包括接收音频数据和音频数据的抄本的计算机实现的方法。 该方法还包括生成包括自动机状态和弧的因子自动机的语言模型,每个自动机弧对应于来自抄本的语言元素。 该方法还包括接收从所接收的音频数据中识别的语言元素以及每个识别的语言元素出现在音频数据中的时间。 该方法还包括将识别的语言元素与因子自动机中的一个或多个语言元素进行比较,以识别音频数据中出现誊本中的一个或多个语言元素的时间。 该方法还包括使用识别的时间将一部分抄本与音频数据的一部分对准。
    • 8. 发明授权
    • System and method for detecting repetitions in a multimedia stream
    • US07065544B2
    • 2006-06-20
    • US09997731
    • 2001-11-29
    • Pedro J. Moreno
    • Pedro J. Moreno
    • G06F17/15
    • G06K9/0055G06F17/30017
    • Large amounts of multimedia data are transmitted over information networks in the form of a digital stream, analog video, or text captioning. Often, repetitions such as paid advertisements, theme music at the commencement of a TV broadcast, and common jingles and slogans occur in these streams. Detection of repetitions in a transmitted signal such as streaming audio or video is described, and includes extracting a plurality of samples from the information stream and accumulating the samples into segments comprising an interval of the transmitted signal. A vector indicative of the samples in each of the segments is generated, and each of the vectors in the segments is correlated to generate a covariance matrix, or signature, corresponding to the segment. Each of the covariance matrices are aggregated into a sequence of covariance matrices and compared to other covariance matrices to generate a distance matrix. The distance matrix includes a distance value, indicative of the similarity between the distance matrices, as a result of the comparing of each matrix. The distance matrix is then traversed to determine similar sequences of covariance matrices.