Automated Assessment of Prosody Production.

Automated Assessment of Prosody Production.
复制标题

DOI:
10.1016/j.specom.2009.04.007
复制
发表时间:
2009-11-01
影响因子:
3.2
通讯作者:
Black, Lois M.
Black, Lois M.
中科院分区:
计算机科学3区
文献类型:
--
作者:
van Santen, Jan P. H.;Prud'hommeaux, Emily Tucker;Black, Lois M.

文献摘要

参考文献

被引文献

相似文献

韵律的评估对于言语和语言障碍的诊断和矫正、神经系统疾病的诊断以及外语教学都是非常重要的。目前的评估主要是认知-感知的,这有明显的缺点;然而,评估的自动化面临着许多障碍。我们提出了自动评估生产的词汇重音,重点,措辞,语用风格和声乐影响的方法。言语分析儿童在六个任务,旨在引起特定的韵律对比。这些方法涉及动态和全局特征,使用谱、基本频率和时间信息。自动计算的分数进行了验证,对平均分数的法官,在所有的任务,但一个,听“韵律最小对”的录音,每对包含两个话语从同一个孩子大致相同的音素材料,但不同的一个特定的韵律尺寸,如压力。法官们识别出两种话语的韵律类别,并对它们的对比强度进行评级。对于几乎所有的任务,我们发现,自动化的分数与平均分数以及法官的个人分数大致相关。在考试过程中分配的实时分数-在语音评估中相当典型-与平均分数的相关性大大低于自动分数。
Assessment of prosody is important for diagnosis and remediation of speech and language disorders, for diagnosis of neurological conditions, and for foreign language instruction. Current assessment is largely auditory-perceptual, which has obvious drawbacks; however, automation of assessment faces numerous obstacles. We propose methods for automatically assessing production of lexical stress, focus, phrasing, pragmatic style, and vocal affect. Speech was analyzed from children in six tasks designed to elicit specific prosodic contrasts. The methods involve dynamic and global features, using spectral, fundamental frequency, and temporal information. The automatically computed scores were validated against mean scores from judges who, in all but one task, listened to “prosodic minimal pairs” of recordings, each pair containing two utterances from the same child with approximately the same phonemic material but differing on a specific prosodic dimension, such as stress. The judges identified the prosodic categories of the two utterances and rated the strength of their contrast. For almost all tasks, we found that the automated scores correlated with the mean scores approximately as well as the judges' individual scores. Real-time scores assigned during examination – as is fairly typical in speech assessment – correlated substantially less than the automated scores with the mean scores.
DOI: 10.1006/jpho.2000.0111
发表时间: 2000-04-01
影响因子: 1.9
作者:
Grabe, E;Post, B;Farrar, K
通讯作者: Farrar, K
自闭症诊断观察表: 提高诊断有效性的修订算法
DOI: 10.1007/s10803-006-0280-1
发表时间: 2007-04-01
影响因子: 3.9
作者:
Gotham, Katherine;Risi, Susan;Lord, Catherine
通讯作者: Lord, Catherine
DOI: 10.1016/0021-9924(83)90026-6
发表时间: 1983-01-01
影响因子: 1.7
作者:
BERK, S;DOEHRING, DG;BRYANS, B
通讯作者: BRYANS, B
DOI: 10.1023/a:1005592401947
发表时间: 2000-06-01
影响因子: 3.9
作者:
Lord, C;Risi, S;Rutter, M
通讯作者: Rutter, M
DOI: 10.1044/jshr.1203.462
发表时间: 1969-01-01
期刊: JOURNAL OF SPEECH AND HEARING RESEARCH
影响因子: --
作者:
DARLEY, FL;ARONSON, AE;BROWN, JR
通讯作者: BROWN, JR