Speech emotion-related analysis needs good emotion corpus. The construction and evaluation of two Tamil emotion corpora, one for children and the other for the adults, are described here. Children emotion speech samples are collected from 30 Tamil movies, and the length of the utterances varies from 5 to 40 s. Tamil audio plays are the resources for building the adult emotion corpus. The emotion prosodies are collected, segmented and annotated for the categories of anger, happy, sad and neutral emotions. Observers’ perception test result has been used to evaluate the annotation of emotion. Automatic emotion classification systems have been built using Gaussian Mixture Model and Support Vector Machine. The database is created with an objective of the acoustic investigation of emotion expression in Tamil, analyzing the influence of speaker's culture and age on emotion expression and investigating the requirement of the need of features unique to Tamil speech on various automatic analysis of speech like emotion recognition, speaker recognition, etc.

与语音情感相关的分析需要良好的情感语料库。这里描述了两种泰米尔语情感语料库的构建和评估，一种用于儿童，另一种用于成人。从30部泰米尔语电影中收集了儿童情感言语样本，话语的长度从5到40 s不等。泰米尔语音频剧是建立成人情感语料库的资源。针对愤怒，快乐，悲伤和中立的情感类别，对情感韵律进行收集，分段和注释。观察者的知觉测试结果已用于评估情感的注释。使用高斯混合模型和支持向量机已经建立了自动情感分类系统。建立该数据库的目的是对泰米尔语中的情绪表达进行声学调查，以分析说话者的影响