Datasets:
Size:
10K<n<100K
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - expert-generated | |
| language: | |
| - de | |
| - en | |
| - es | |
| - fr | |
| - it | |
| license: | |
| - cc-by-sa-4.0 | |
| multilinguality: | |
| - multilingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-generation | |
| - fill-mask | |
| - text-classification | |
| task_ids: | |
| - dialogue-modeling | |
| - language-modeling | |
| - masked-language-modeling | |
| - text-classification-other-dialogue-act-classification | |
| paperswithcode_id: null | |
| pretty_name: MIAM | |
| configs: | |
| - dihana | |
| - ilisten | |
| - loria | |
| - maptask | |
| - vm2 | |
| # Dataset Card for MIAM | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [N/A] | |
| - **Repository:** [N/A] | |
| - **Paper:** [N/A] | |
| - **Leaderboard:** [N/A] | |
| - **Point of Contact:** [N/A] | |
| ### Dataset Summary | |
| Multilingual dIalogAct benchMark is a collection of resources for training, evaluating, and | |
| analyzing natural language understanding systems specifically designed for spoken language. Datasets | |
| are in English, French, German, Italian and Spanish. They cover a variety of domains including | |
| spontaneous speech, scripted scenarios, and joint task completion. All datasets contain dialogue act | |
| labels. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| English, French, German, Italian, Spanish. | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### Dihana Corpus | |
| For the `dihana` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'U', | |
| 'Utterance': 'Hola , quería obtener el horario para ir a Valencia', | |
| 'Dialogue_Act': 9, # 'Pregunta' ('Request') | |
| 'Dialogue_ID': '0', | |
| 'File_ID': 'B209_BA5c3', | |
| } | |
| ``` | |
| #### iLISTEN Corpus | |
| For the `ilisten` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'T_11_U11', | |
| 'Utterance': 'ok, grazie per le informazioni', | |
| 'Dialogue_Act': 6, # 'KIND-ATTITUDE_SMALL-TALK' | |
| 'Dialogue_ID': '0', | |
| } | |
| ``` | |
| #### LORIA Corpus | |
| For the `loria` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'Samir', | |
| 'Utterance': 'Merci de votre visite, bonne chance, et à la prochaine !', | |
| 'Dialogue_Act': 21, # 'quit' | |
| 'Dialogue_ID': '5', | |
| 'File_ID': 'Dial_20111128_113927', | |
| } | |
| ``` | |
| #### HCRC MapTask Corpus | |
| For the `maptask` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'f', | |
| 'Utterance': 'is it underneath the rope bridge or to the left', | |
| 'Dialogue_Act': 6, # 'query_w' | |
| 'Dialogue_ID': '0', | |
| 'File_ID': 'q4ec1', | |
| } | |
| ``` | |
| #### VERBMOBIL | |
| For the `vm2` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Utterance': 'ja was sind viereinhalb Stunden Bahngerüttel gegen siebzig Minuten Turbulenzen im Flugzeug', | |
| 'Utterance': 'Utterance', | |
| 'Dialogue_Act': 'Dialogue_Act', # 'INFORM' | |
| 'Speaker': 'A', | |
| 'Dialogue_ID': '66', | |
| } | |
| ``` | |
| ### Data Fields | |
| For the `dihana` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'Afirmacion' (0) [Feedback_positive], 'Apertura' (1) [Opening], 'Cierre' (2) [Closing], 'Confirmacion' (3) [Acknowledge], 'Espera' (4) [Hold], 'Indefinida' (5) [Undefined], 'Negacion' (6) [Feedback_negative], 'No_entendido' (7) [Request_clarify], 'Nueva_consulta' (8) [New_request], 'Pregunta' (9) [Request] or 'Respuesta' (10) [Reply]. | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `ilisten` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'AGREE' (0), 'ANSWER' (1), 'CLOSING' (2), 'ENCOURAGE-SORRY' (3), 'GENERIC-ANSWER' (4), 'INFO-REQUEST' (5), 'KIND-ATTITUDE_SMALL-TALK' (6), 'OFFER-GIVE-INFO' (7), 'OPENING' (8), 'PERSUASION-SUGGEST' (9), 'QUESTION' (10), 'REJECT' (11), 'SOLICITATION-REQ_CLARIFICATION' (12), 'STATEMENT' (13) or 'TALK-ABOUT-SELF' (14). | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| For the `loria` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'ack' (0), 'ask' (1), 'find_mold' (2), 'find_plans' (3), 'first_step' (4), 'greet' (5), 'help' (6), 'inform' (7), 'inform_engine' (8), 'inform_job' (9), 'inform_material_space' (10), 'informer_conditioner' (11), 'informer_decoration' (12), 'informer_elcomps' (13), 'informer_end_manufacturing' (14), 'kindAtt' (15), 'manufacturing_reqs' (16), 'next_step' (17), 'no' (18), 'other' (19), 'quality_control' (20), 'quit' (21), 'reqRep' (22), 'security_policies' (23), 'staff_enterprise' (24), 'staff_job' (25), 'studies_enterprise' (26), 'studies_job' (27), 'todo_failure' (28), 'todo_irreparable' (29), 'yes' (30) | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `maptask` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'acknowledge' (0), 'align' (1), 'check' (2), 'clarify' (3), 'explain' (4), 'instruct' (5), 'query_w' (6), 'query_yn' (7), 'ready' (8), 'reply_n' (9), 'reply_w' (10) or 'reply_y' (11). | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `vm2` configuration, the different fields are: | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialogue act label of the utterance. It can be one of 'ACCEPT' (0), 'BACKCHANNEL' (1), 'BYE' (2), 'CLARIFY' (3), 'CLOSE' (4), 'COMMIT' (5), 'CONFIRM' (6), 'DEFER' (7), 'DELIBERATE' (8), 'DEVIATE_SCENARIO' (9), 'EXCLUDE' (10), 'EXPLAINED_REJECT' (11), 'FEEDBACK' (12), 'FEEDBACK_NEGATIVE' (13), 'FEEDBACK_POSITIVE' (14), 'GIVE_REASON' (15), 'GREET' (16), 'INFORM' (17), 'INIT' (18), 'INTRODUCE' (19), 'NOT_CLASSIFIABLE' (20), 'OFFER' (21), 'POLITENESS_FORMULA' (22), 'REJECT' (23), 'REQUEST' (24), 'REQUEST_CLARIFY' (25), 'REQUEST_COMMENT' (26), 'REQUEST_COMMIT' (27), 'REQUEST_SUGGEST' (28), 'SUGGEST' (29), 'THANK' (30). | |
| - `Speaker`: Speaker as a string. | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| ### Data Splits | |
| | Dataset name | Train | Valid | Test | | |
| | ------------ | ----- | ----- | ---- | | |
| | dihana | 19063 | 2123 | 2361 | | |
| | ilisten | 1986 | 230 | 971 | | |
| | loria | 8465 | 942 | 1047 | | |
| | maptask | 25382 | 5221 | 5335 | | |
| | vm2 | 25060 | 2860 | 2855 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Benchmark Curators | |
| Anonymous | |
| ### Licensing Information | |
| This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Unported License](https://creativecommons.org/licenses/by-sa/4.0/). | |
| ### Citation Information | |
| ``` | |
| @unpublished{ | |
| anonymous2021cross-lingual, | |
| title={Cross-Lingual Pretraining Methods for Spoken Dialog}, | |
| author={Anonymous}, | |
| journal={OpenReview Preprint}, | |
| year={2021}, | |
| url{https://openreview.net/forum?id=c1oDhu_hagR}, | |
| note={anonymous preprint under review} | |
| } | |
| ``` | |