公开(公告)号：US20100312556A1

公开(公告)日：2010-12-09

申请号：US12480864

申请日：2009-06-09

Applicant: Andrej LJOLJE ,  Alistair D. CONKIE ,  Ann K. SYRDAL

Inventor： Andrej LJOLJE ,  Alistair D. CONKIE ,  Ann K. SYRDAL

IPC: G10L15/06

CPC classification number: G10L15/07 ,  G10L15/10 ,  G10L15/265

Abstract: Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for speaker recognition personalization. The method recognizes speech received from a speaker interacting with a speech interface using a set of allocated resources, the set of allocated resources including bandwidth, processor time, memory, and storage. The method records metrics associated with the recognized speech, and after recording the metrics, modifies at least one of the allocated resources in the set of allocated resources commensurate with the recorded metrics. The method recognizes additional speech from the speaker using the modified set of allocated resources. Metrics can include a speech recognition confidence score, processing speed, dialog behavior, requests for repeats, negative responses to confirmations, and task completions. The method can further store a speaker personalization profile having information for the modified set of allocated resources and recognize speech associated with the speaker based on the speaker personalization profile.

Abstract translation: 这里公开了用于说话人识别个性化的系统，计算机实现的方法和有形的计算机可读存储介质。 该方法使用一组分配的资源来识别从与语音接口交互的扬声器接收的语音，所分配的资源的集合包括带宽，处理器时间，存储器和存储。 该方法记录与识别的语音相关联的度量，并且在记录度量之后，修改与记录的度量相称的所分配资源集合中的所分配的资源中的至少一个。 该方法使用经修改的分配资源集来识别来自扬声器的附加语音。 指标可以包括语音识别置信度分数，处理速度，对话行为，重复请求，对确认的否定响应以及任务完成。 该方法还可以存储具有用于所修改的分配资源集合的信息的扬声器个性化简档，并且基于说话者个性化简档识别与说话者相关联的语音。

公开(公告)号：US20100312560A1

公开(公告)日：2010-12-09

申请号：US12480848

申请日：2009-06-09

Applicant: Andrej LJOLJE ,  Alistair D. CONKIE ,  Ann K. SYRDAL

Inventor： Andrej LJOLJE ,  Alistair D. CONKIE ,  Ann K. SYRDAL

IPC: G10L15/02

CPC classification number: G10L17/14 ,  G10L15/063 ,  G10L15/07 ,  G10L15/14 ,  G10L15/187 ,  G10L15/265 ,  G10L15/30 ,  G10L2015/025

Abstract: Disclosed herein are systems, computer-implemented methods, and computer-readable storage media for recognizing speech by adapting automatic speech recognition pronunciation by acoustic model restructuring. The method identifies an acoustic model and a matching pronouncing dictionary trained on typical native speech in a target dialect. The method collects speech from a new speaker resulting in collected speech and transcribes the collected speech to generate a lattice of plausible phonemes. Then the method creates a custom speech model for representing each phoneme used in the pronouncing dictionary by a weighted sum of acoustic models for all the plausible phonemes, wherein the pronouncing dictionary does not change, but the model of the acoustic space for each phoneme in the dictionary becomes a weighted sum of the acoustic models of phonemes of the typical native speech. Finally the method includes recognizing via a processor additional speech from the target speaker using the custom speech model.

Abstract translation: 这里公开的是系统，计算机实现的方法和用于通过声学模型重构来适应自动语音识别发音来识别语音的计算机可读存储介质。 该方法识别在目标方言中典型的本地语音训练的声学模型和匹配的发音字典。 该方法从新的演讲者收集演讲，从而收集到的演讲并转录收集的演讲，以产生一个合理的音素格子。 然后，该方法创建一个自定义语音模型，用于通过用于所有似乎合理的音素的声学模型的加权和来表示在发音字典中使用的每个音素，其中发音字典不改变，而是在每个音素的声学空间的模型中 字典成为典型本地语音的音素的声学模型的加权和。 最后，该方法包括使用定制语音模型通过处理器从目标说话者识别附加语音。

公开(公告)号：US20120035917A1

公开(公告)日：2012-02-09

申请号：US12852146

申请日：2010-08-06

Applicant: Yeon-Jun KIM ,  Mark Charles BEUTNAGEL ,  Alistair D. CONKIE ,  Ann K. SYRDAL

Inventor： Yeon-Jun KIM ,  Mark Charles BEUTNAGEL ,  Alistair D. CONKIE ,  Ann K. SYRDAL

IPC: G10L19/00

CPC classification number: G10L13/033 ,  G10L13/027 ,  G10L13/043 ,  G10L13/10 ,  G10L15/1807 ,  G10L25/00

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for detecting and correcting abnormal stress patterns in unit-selection speech synthesis. A system practicing the method detects incorrect stress patterns in selected acoustic units representing speech to be synthesized, and corrects the incorrect stress patterns in the selected acoustic units to yield corrected stress patterns. The system can further synthesize speech based on the corrected stress patterns. In one aspect, the system also classifies the incorrect stress patterns using a machine learning algorithm such as a classification and regression tree, adaptive boosting, support vector machine, and maximum entropy. In this way a text-to-speech unit selection speech synthesizer can produce more natural sounding speech with suitable stress patterns regardless of the stress of units in a unit selection database.

Abstract translation: 这里公开了用于在单位选择语音合成中检测和校正异常应力模式的系统，方法和非暂时的计算机可读存储介质。 实施该方法的系统检测表示要合成的语音的所选声学单元中的不正确应力模式，并且校正所选声学单元中的不正确应力模式以产生校正的应力模式。 该系统可以基于校正的应力模式进一步合成语音。 在一个方面，系统还使用诸如分类和回归树，自适应增强，支持向量机和最大熵的机器学习算法对不正确的应力模式进行分类。 以这种方式，文本到语音单元选择语音合成器可以产生具有合适的应力模式的更自然的声音语音，而不管单元选择数据库中的单元的应力。

公开(公告)号：US20110071836A1

公开(公告)日：2011-03-24

申请号：US12563654

申请日：2009-09-21

Applicant: Alistair D. CONKIE ,  Mark BEUTNAGEL ,  Yeon-Jun KIM ,  Ann K. SYRDAL

Inventor： Alistair D. CONKIE ,  Mark BEUTNAGEL ,  Yeon-Jun KIM ,  Ann K. SYRDAL

IPC: G10L13/06

CPC classification number: G10L13/06 ,  G10L13/00 ,  G10L13/047

Abstract: Disclosed herein are systems, computer-implemented methods, and computer-readable storage media for unit selection synthesis. The method causes a computing device to add a supplemental phoneset to a speech synthesizer front end having an existing phoneset, modify a unit preselection process based on the supplemental phoneset, preselect units from the supplemental phoneset and the existing phoneset based on the modified unit preselection process, and generate speech based on the preselected units. The supplemental phoneset can be a variation of the existing phoneset, can include a word boundary feature, can include a cluster feature where initial consonant clusters and some word boundaries are marked with diacritics, can include a function word feature which marks units as originating from a function word or a content word, and/or can include a pre-vocalic or post-vocalic feature. The speech synthesizer front end can incorporates the supplemental phoneset as an extra feature.

Abstract translation: 本文公开了用于单元选择合成的系统，计算机实现的方法和计算机可读存储介质。 该方法使得计算设备将辅助电话机添加到具有现有电话机的语音合成器前端，基于补充电话机修改单元预选过程，基于修改的单位预选过程从辅助电话机和现有电话机中预选单元 ，并根据预选单位产生语音。 补充手机可以是现有手机的变体，可以包括字边界特征，可以包括其中初始辅音簇和一些字边界用变音符标记的群集特征，可以包括将单位标记为源自于 功能词或内容词，和/或可以包括语音前或后声部特征。 语音合成器前端可以将补充的电话机作为额外的功能。

公开(公告)号：US20120281885A1

公开(公告)日：2012-11-08

申请号：US13101704

申请日：2011-05-05

Applicant: Ann K. SYRDAL ,  Sumit Chopra ,  Patrick Haffner ,  Taniya Mishra ,  Ilija Zeljkovic ,  Eric Zavesky

Inventor： Ann K. SYRDAL ,  Sumit Chopra ,  Patrick Haffner ,  Taniya Mishra ,  Ilija Zeljkovic ,  Eric Zavesky

IPC: G06K9/00

CPC classification number: G10L15/25 ,  G06F21/32 ,  G06F2221/2103 ,  G06K9/00255 ,  G06K9/00281 ,  G06K9/00288 ,  G06K9/00315 ,  G06K9/00335 ,  G10L17/24 ,  G10L21/06

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for performing speaker verification. A system configured to practice the method receives a request to verify a speaker, generates a text challenge that is unique to the request, and, in response to the request, prompts the speaker to utter the text challenge. Then the system records a dynamic image feature of the speaker as the speaker utters the text challenge, and performs speaker verification based on the dynamic image feature and the text challenge. Recording the dynamic image feature of the speaker can include recording video of the speaker while speaking the text challenge. The dynamic feature can include a movement pattern of head, lips, mouth, eyes, and/or eyebrows of the speaker. The dynamic image feature can relate to phonetic content of the speaker speaking the challenge, speech prosody, and the speaker's facial expression responding to content of the challenge.

Abstract translation: 本文公开了用于执行说话者验证的系统，方法和非暂时的计算机可读存储介质。 被配置为实施该方法的系统接收到验证说话者的请求，产生对该请求是唯一的文本挑战，并且响应该请求提示说话者发出文本挑战。 然后当扬声器发出文本挑战时，系统记录扬声器的动态图像特征，并且基于动态图像特征和文本挑战来执行说话者验证。 录制扬声器的动态图像功能可以包括在说出文本挑战时录制扬声器的视频。 动态特征可以包括扬声器的头部，嘴唇，嘴巴，眼睛和/或眉毛的运动模式。 动态图像特征可以涉及讲话者讲话的语音内容，语音韵律以及响应于挑战内容的说话者的面部表情。