ntnu-smil/LTTC-Train1964-0520

该数据集是一个包含语音相关特征的训练数据集，具体内容未在README中描述，但根据字段名称和类型推测，可能包含了说话者ID、表格ID、评分、分类、语音识别转录文本、音频路径、提示文本、示例文本、置信度分数、声学分数、语言模型分数、音高、强度、停顿时间、静默时间、持续时间、每分钟单词数、总单词数、级别分数、序列长度、关键字分数、平均值、总平均分数、阈值计数、平均音高、平均强度、持续时间、本地抖动、本地闪耀、抖动、长静默、静默、长静默数、静默数、能量标准差、平均频谱、平均能量熵、零交叉数、语音与无声比例、语音计数、无声计数、平均长静默、平均静默、三个以上单词的数量、单词数、语音识别转录文本、表达向量、句子数、uh词计数、静默数、长静默数等特征。数据集分为训练集，并提供了相关文件大小和示例数量信息。

This dataset is a training dataset containing speech-related features, with no specific description provided in the README. Based on the field names and types, it is speculated to include features such as speaker ID, form ID, rating, classification, ASR transcription text, audio path, prompt text, example text, confidence score, acoustic score, language model score, pitch, intensity, pause time, silence time, duration, words per minute, total number of words, level scores, sequence length, key scores, average value, overall average score, threshold count, mean pitch, mean intensity, duration, local jitter, local shimmer, rap jitter, long silence, silence, number of long silences, number of silences, standard deviation of energy, average spectrum, average energy entropy, zero crossing number, voice to unvoice ratio, voice count, unvoice count, mean long silence, mean silence, number of words with more than three characters, number of words, whisperX transcription, delivery vector, number of sentences, uh count, number of silences, number of long silences, etc. The dataset is split into a training set and provides related file size and example count information.