Patent application number | Description | Published |
20120016672 | Systems and Methods for Assessment of Non-Native Speech Using Vowel Space Characteristics - Computer-implemented systems and methods are provided for assessing non-native speech proficiency. A non-native speech sample is processed to identify a plurality of vowel sound boundaries in the non-native speech sample. Portions of the non-native speech sample are analyzed within the vowel sound boundaries to extract vowel characteristics. The vowel characteristics are used to identify a plurality of vowel space metrics for the non-native speech sample, and the vowel space metrics are used to determine a non-native speech proficiency score for the non-native speech sample. | 01-19-2012 |
20120323573 | Non-Scorable Response Filters For Speech Scoring Systems - A method for scoring non-native speech includes receiving a speech sample spoken by a non-native speaker and performing automatic speech recognition and metric extraction on the speech sample to generate a transcript of the speech sample and a speech metric associated with the speech sample. The method further includes determining whether the speech sample is scorable or non-scorable based upon the transcript and speech metric, where the determination is based on an audio quality of the speech sample, an amount of speech of the speech sample, a degree to which the speech sample is off-topic, whether the speech sample includes speech from an incorrect language, or whether the speech sample includes plagiarized material. When the sample is determined to be non-scorable, an indication of non-scorability is associated with the speech sample. When the sample is determined to be scorable, the sample is provided to a scoring model for scoring. | 12-20-2012 |
20130158982 | Computer-Implemented Systems and Methods for Content Scoring of Spoken Responses - Systems and methods are provided for scoring a non-scripted speech sample. A system includes one or more data processors and one or more computer-readable mediums. The computer-readable mediums are encoded with a non-scripted speech sample data structure, where the non-scripted speech sample data structure includes: a speech sample identifier that identifies a non-scripted speech sample, a content feature extracted from the non-scripted speech sample, and a content-based speech score for the non-scripted speech sample. The computer-readable mediums further include instructions for commanding the one or more data processors to extract the content feature from a set of words automatically recognized in the non-scripted speech sample and to score the non-scripted speech sample by providing the extracted content feature to a scoring model to generate the content-based speech score. | 06-20-2013 |
20140195239 | Systems and Methods for an Automated Pronunciation Assessment System for Similar Vowel Pairs - Computer-implemented systems and methods are provided for assessing non-native speech proficiency. a non-native speech sample is processed to identify a plurality of vowel sound boundaries in the non-native speech sample. Portions of the non-native speech sample are analyzed within the vowel sound boundaries to extract vowel characteristics associated with a first vowel sound and a second vowel sound represented in the non-native speech sample. The vowel characteristics are processed to identify a first vowel pronunciation metric for the first vowel sound and a second vowel pronunciation metric for the second vowel sound, and the first vowel pronunciation metric and the second vowel pronunciation metric are processed to determine whether the non-native speech sample exhibits a distinction in pronunciation of the first vowel sound and the second vowel sound. | 07-10-2014 |
20140278376 | Systems and Methods for Generating Recitation Items - Computer-implemented systems and methods are provided for automatically generating recitation items. For example, a computer performing the recitation item generation can receive one or more text sets that each includes one or more texts. The computer can determine a value for each text set using one or more metrics, such as a vocabulary difficulty metric, a syntactic complexity metric, a phoneme distribution metric, a phonetic difficulty metric, and a prosody distribution metric. Then the computer can select a final text set based on the value associated with each text set. The selected final text set can be used as the recitation items for a speaking assessment test. | 09-18-2014 |
20140297277 | Systems and Methods for Automated Scoring of Spoken Language in Multiparty Conversations - Systems and methods are provided for scoring spoken language in multiparty conversations. A computer receives a conversation between an examinee and at least one interlocutor. The computer selects a portion of the conversation. The portion includes one or more examinee utterances and one or more interlocutor utterances. The computer assesses the portion using one or more metrics, such as: a pragmatic metric for measuring a pragmatic fit of the one or more examinee utterances; a speech act metric for measuring a speech act appropriateness of the one or more examinee utterances; a speech register metric for measuring a speech register appropriateness of the one or more examinee utterances; and an accommodation metric for measuring a level of accommodation of the one or more examinee utterances. The computer computes a final score for the portion of the conversation based on the one or more metrics applied. | 10-02-2014 |