Datasets:
miam

	---
	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
	pretty_name: MIAM
	tags:
	- dialogue-act-classification
	dataset_info:
	- config_name: dihana
	features:
	- name: Speaker
	dtype: string
	- name: Utterance
	dtype: string
	- name: Dialogue_Act
	dtype: string
	- name: Dialogue_ID
	dtype: string
	- name: File_ID
	dtype: string
	- name: Label
	dtype:
	class_label:
	names:
	'0': Afirmacion
	'1': Apertura
	'2': Cierre
	'3': Confirmacion
	'4': Espera
	'5': Indefinida
	'6': Negacion
	'7': No_entendido
	'8': Nueva_consulta
	'9': Pregunta
	'10': Respuesta
	- name: Idx
	dtype: int32
	splits:
	- name: train
	num_bytes: 1946735
	num_examples: 19063
	- name: validation
	num_bytes: 216498
	num_examples: 2123
	- name: test
	num_bytes: 238446
	num_examples: 2361
	download_size: 1777267
	dataset_size: 2401679
	- config_name: ilisten
	features:
	- name: Speaker
	dtype: string
	- name: Utterance
	dtype: string
	- name: Dialogue_Act
	dtype: string
	- name: Dialogue_ID
	dtype: string
	- name: Label
	dtype:
	class_label:
	names:
	'0': AGREE
	'1': ANSWER
	'2': CLOSING
	'3': ENCOURAGE-SORRY
	'4': GENERIC-ANSWER
	'5': INFO-REQUEST
	'6': KIND-ATTITUDE_SMALL-TALK
	'7': OFFER-GIVE-INFO
	'8': OPENING
	'9': PERSUASION-SUGGEST
	'10': QUESTION
	'11': REJECT
	'12': SOLICITATION-REQ_CLARIFICATION
	'13': STATEMENT
	'14': TALK-ABOUT-SELF
	- name: Idx
	dtype: int32
	splits:
	- name: train
	num_bytes: 244336
	num_examples: 1986
	- name: validation
	num_bytes: 33988
	num_examples: 230
	- name: test
	num_bytes: 145376
	num_examples: 971
	download_size: 349993
	dataset_size: 423700
	- config_name: loria
	features:
	- name: Speaker
	dtype: string
	- name: Utterance
	dtype: string
	- name: Dialogue_Act
	dtype: string
	- name: Dialogue_ID
	dtype: string
	- name: File_ID
	dtype: string
	- name: Label
	dtype:
	class_label:
	names:
	'0': ack
	'1': ask
	'2': find_mold
	'3': find_plans
	'4': first_step
	'5': greet
	'6': help
	'7': inform
	'8': inform_engine
	'9': inform_job
	'10': inform_material_space
	'11': informer_conditioner
	'12': informer_decoration
	'13': informer_elcomps
	'14': informer_end_manufacturing
	'15': kindAtt
	'16': manufacturing_reqs
	'17': next_step
	'18': 'no'
	'19': other
	'20': quality_control
	'21': quit
	'22': reqRep
	'23': security_policies
	'24': staff_enterprise
	'25': staff_job
	'26': studies_enterprise
	'27': studies_job
	'28': todo_failure
	'29': todo_irreparable
	'30': 'yes'
	- name: Idx
	dtype: int32
	splits:
	- name: train
	num_bytes: 1208730
	num_examples: 8465
	- name: validation
	num_bytes: 133829
	num_examples: 942
	- name: test
	num_bytes: 149855
	num_examples: 1047
	download_size: 1221132
	dataset_size: 1492414
	- config_name: maptask
	features:
	- name: Speaker
	dtype: string
	- name: Utterance
	dtype: string
	- name: Dialogue_Act
	dtype: string
	- name: Dialogue_ID
	dtype: string
	- name: File_ID
	dtype: string
	- name: Label
	dtype:
	class_label:
	names:
	'0': acknowledge
	'1': align
	'2': check
	'3': clarify
	'4': explain
	'5': instruct
	'6': query_w
	'7': query_yn
	'8': ready
	'9': reply_n
	'10': reply_w
	'11': reply_y
	- name: Idx
	dtype: int32
	splits:
	- name: train
	num_bytes: 1910120
	num_examples: 25382
	- name: validation
	num_bytes: 389879
	num_examples: 5221
	- name: test
	num_bytes: 396947
	num_examples: 5335
	download_size: 1729021
	dataset_size: 2696946
	- config_name: vm2
	features:
	- name: Utterance
	dtype: string
	- name: Dialogue_Act
	dtype: string
	- name: Speaker
	dtype: string
	- name: Dialogue_ID
	dtype: string
	- name: Label
	dtype:
	class_label:
	names:
	'0': ACCEPT
	'1': BACKCHANNEL
	'2': BYE
	'3': CLARIFY
	'4': CLOSE
	'5': COMMIT
	'6': CONFIRM
	'7': DEFER
	'8': DELIBERATE
	'9': DEVIATE_SCENARIO
	'10': EXCLUDE
	'11': EXPLAINED_REJECT
	'12': FEEDBACK
	'13': FEEDBACK_NEGATIVE
	'14': FEEDBACK_POSITIVE
	'15': GIVE_REASON
	'16': GREET
	'17': INFORM
	'18': INIT
	'19': INTRODUCE
	'20': NOT_CLASSIFIABLE
	'21': OFFER
	'22': POLITENESS_FORMULA
	'23': REJECT
	'24': REQUEST
	'25': REQUEST_CLARIFY
	'26': REQUEST_COMMENT
	'27': REQUEST_COMMIT
	'28': REQUEST_SUGGEST
	'29': SUGGEST
	'30': THANK
	- name: Idx
	dtype: int32
	splits:
	- name: train
	num_bytes: 1869254
	num_examples: 25060
	- name: validation
	num_bytes: 209390
	num_examples: 2860
	- name: test
	num_bytes: 209032
	num_examples: 2855
	download_size: 1641453
	dataset_size: 2287676
	config_names:
	- 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

	### Dataset 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

	```
	@inproceedings{colombo-etal-2021-code,
	title = "Code-switched inspired losses for spoken dialog representations",
	author = "Colombo, Pierre and
	Chapuis, Emile and
	Labeau, Matthieu and
	Clavel, Chlo{\'e}",
	booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
	month = nov,
	year = "2021",
	address = "Online and Punta Cana, Dominican Republic",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2021.emnlp-main.656",
	doi = "10.18653/v1/2021.emnlp-main.656",
	pages = "8320--8337",
	abstract = "Spoken dialogue systems need to be able to handle both multiple languages and multilinguality inside a conversation (\textit{e.g} in case of code-switching). In this work, we introduce new pretraining losses tailored to learn generic multilingual spoken dialogue representations. The goal of these losses is to expose the model to code-switched language. In order to scale up training, we automatically build a pretraining corpus composed of multilingual conversations in five different languages (French, Italian, English, German and Spanish) from OpenSubtitles, a huge multilingual corpus composed of 24.3G tokens. We test the generic representations on MIAM, a new benchmark composed of five dialogue act corpora on the same aforementioned languages as well as on two novel multilingual tasks (\textit{i.e} multilingual mask utterance retrieval and multilingual inconsistency identification). Our experiments show that our new losses achieve a better performance in both monolingual and multilingual settings.",
	}
	```

	### Contributions

	Thanks to [@eusip](https://github.com/eusip) and [@PierreColombo](https://github.com/PierreColombo) for adding this dataset.