Speech Sentiment Annotations
|Item Name:||Speech Sentiment Annotations|
|Author(s):||Eric Y. Chen, Zhiyun Lu, Hao Xu, Liangliang Cao, Yu Zhang, James Fan|
|LDC Catalog No.:||LDC2020T14|
|Release Date:||July 15, 2020|
|Data Source(s):||telephone conversations|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2020T14 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Chen, Eric Y., et al. Speech Sentiment Annotations LDC2020T14. Web Download. Philadelphia: Linguistic Data Consortium, 2020.|
Speech Sentiment Annotations was developed by Google Inc. It consists of sentiment labels (positive, negative, neutral) for approximately 49,500 utterances covering 140 hours of audio from Switchboard-1 Release 2 (LDC97S62).
Switchboard-1 Release 2 consists of approximately 260 hours of telephone speech from 543 speakers across the United States (302 male speakers, 241 female speakers). A computer-driven telephone collection platform paired two subjects for each conversation and provided a discussion topic. No two speakers conversed together more than once and no one speaker talked more than once on a given topic.
Switchboard speech files were segmented based on the start and end time of transcript turns. Annotators listened to the audio corresponding to each segment (utterance) and classified each into positive, negative or neutral categories based on the emotion and attitude of the speaker. Annotators provided a justification for positive and negative classifications using a flow chart. Further information about the methodology and annotation process is contained in the documentation accompanying this release.
The data is stored as a single UTF-8 encoded tab-delimited file. The annotation column in each row includes judgments from at least three annotators.
Please view the following sample (TXT).
None at this time.