Datasets:

FBK-MT
/

Speech-MASSIVE

	---
	annotations_creators:
	- crowdsourced
	language_creators:
	- found
	language:
	- ar
	- de
	- es
	- fr
	- hu
	- ko
	- nl
	- pl
	- pt
	- ru
	- tr
	- vi
	license:
	- cc-by-nc-sa-4.0
	multilinguality:
	- multilingual
	size_categories:
	- 10K<n<100K
	source_datasets:
	- extended
	task_categories:
	- audio-classification
	- text-classification
	- zero-shot-classification
	- automatic-speech-recognition
	task_ids: []
	pretty_name: A Multilingual Speech Dataset for SLU and Beyond
	tags:
	- spoken language understanding
	- slot filling
	- intent classification
	- speech translation
	- speaker identification
	dataset_info:
	- config_name: all
	features:
	- name: id
	dtype: string
	- name: locale
	dtype: string
	- name: partition
	dtype: string
	- name: scenario
	dtype:
	class_label:
	names:
	'0': social
	'1': transport
	'2': calendar
	'3': play
	'4': news
	'5': datetime
	'6': recommendation
	'7': email
	'8': iot
	'9': general
	'10': audio
	'11': lists
	'12': qa
	'13': cooking
	'14': takeaway
	'15': music
	'16': alarm
	'17': weather
	- name: scenario_str
	dtype: string
	- name: intent_idx
	dtype:
	class_label:
	names:
	'0': datetime_query
	'1': iot_hue_lightchange
	'2': transport_ticket
	'3': takeaway_query
	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
	'40': iot_hue_lightoff
	'41': iot_hue_lighton
	'42': transport_query
	'43': music_likeness
	'44': email_query
	'45': play_music
	'46': audio_volume_mute
	'47': social_post
	'48': alarm_set
	'49': qa_factoid
	'50': calendar_set
	'51': play_game
	'52': alarm_remove
	'53': lists_remove
	'54': transport_taxi
	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
	- name: intent_str
	dtype: string
	- name: utt
	dtype: string
	- name: annot_utt
	dtype: string
	- name: worker_id
	dtype: string
	- name: slot_method
	sequence:
	- name: slot
	dtype: string
	- name: method
	dtype: string
	- name: judgments
	sequence:
	- name: worker_id
	dtype: string
	- name: intent_score
	dtype: int8
	- name: slots_score
	dtype: int8
	- name: grammar_score
	dtype: int8
	- name: spelling_score
	dtype: int8
	- name: language_identification
	dtype: string
	- name: tokens
	sequence: string
	- name: labels
	sequence: string
	- name: audio
	dtype:
	audio:
	sampling_rate: 16000
	- name: path
	dtype: string
	- name: is_transcript_reported
	dtype: bool
	- name: is_validated
	dtype: bool
	- name: speaker_id
	dtype: string
	- name: speaker_sex
	dtype: string
	- name: speaker_age
	dtype: string
	- name: speaker_ethnicity_simple
	dtype: string
	- name: speaker_country_of_birth
	dtype: string
	- name: speaker_country_of_residence
	dtype: string
	- name: speaker_nationality
	dtype: string
	- name: speaker_first_language
	dtype: string
	splits:
	- name: train_115
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	num_examples: 1380
	- name: validation
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	num_examples: 24396
	- name: train
	num_bytes: 8663179158.0
	num_examples: 23028
	download_size: 23732148508
	dataset_size: 18429418934.0
	- config_name: ar-SA
	features:
	- name: id
	dtype: string
	- name: locale
	dtype: string
	- name: partition
	dtype: string
	- name: scenario
	dtype:
	class_label:
	names:
	'0': social
	'1': transport
	'2': calendar
	'3': play
	'4': news
	'5': datetime
	'6': recommendation
	'7': email
	'8': iot
	'9': general
	'10': audio
	'11': lists
	'12': qa
	'13': cooking
	'14': takeaway
	'15': music
	'16': alarm
	'17': weather
	- name: scenario_str
	dtype: string
	- name: intent_idx
	dtype:
	class_label:
	names:
	'0': datetime_query
	'1': iot_hue_lightchange
	'2': transport_ticket
	'3': takeaway_query
	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
	'40': iot_hue_lightoff
	'41': iot_hue_lighton
	'42': transport_query
	'43': music_likeness
	'44': email_query
	'45': play_music
	'46': audio_volume_mute
	'47': social_post
	'48': alarm_set
	'49': qa_factoid
	'50': calendar_set
	'51': play_game
	'52': alarm_remove
	'53': lists_remove
	'54': transport_taxi
	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
	- name: intent_str
	dtype: string
	- name: utt
	dtype: string
	- name: annot_utt
	dtype: string
	- name: worker_id
	dtype: string
	- name: slot_method
	sequence:
	- name: slot
	dtype: string
	- name: method
	dtype: string
	- name: judgments
	sequence:
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	dtype: string
	- name: intent_score
	dtype: int8
	- name: slots_score
	dtype: int8
	- name: grammar_score
	dtype: int8
	- name: spelling_score
	dtype: int8
	- name: language_identification
	dtype: string
	- name: tokens
	sequence: string
	- name: labels
	sequence: string
	- name: audio
	dtype:
	audio:
	sampling_rate: 16000
	- name: path
	dtype: string
	- name: is_transcript_reported
	dtype: bool
	- name: is_validated
	dtype: bool
	- name: speaker_id
	dtype: string
	- name: speaker_sex
	dtype: string
	- name: speaker_age
	dtype: string
	- name: speaker_ethnicity_simple
	dtype: string
	- name: speaker_country_of_birth
	dtype: string
	- name: speaker_country_of_residence
	dtype: string
	- name: speaker_nationality
	dtype: string
	- name: speaker_first_language
	dtype: string
	splits:
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	num_examples: 115
	- name: validation
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	num_examples: 2033
	download_size: 1393604308
	dataset_size: 783994663.0
	- config_name: de-DE
	features:
	- name: id
	dtype: string
	- name: locale
	dtype: string
	- name: partition
	dtype: string
	- name: scenario
	dtype:
	class_label:
	names:
	'0': social
	'1': transport
	'2': calendar
	'3': play
	'4': news
	'5': datetime
	'6': recommendation
	'7': email
	'8': iot
	'9': general
	'10': audio
	'11': lists
	'12': qa
	'13': cooking
	'14': takeaway
	'15': music
	'16': alarm
	'17': weather
	- name: scenario_str
	dtype: string
	- name: intent_idx
	dtype:
	class_label:
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	'1': iot_hue_lightchange
	'2': transport_ticket
	'3': takeaway_query
	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
	'40': iot_hue_lightoff
	'41': iot_hue_lighton
	'42': transport_query
	'43': music_likeness
	'44': email_query
	'45': play_music
	'46': audio_volume_mute
	'47': social_post
	'48': alarm_set
	'49': qa_factoid
	'50': calendar_set
	'51': play_game
	'52': alarm_remove
	'53': lists_remove
	'54': transport_taxi
	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
	- name: intent_str
	dtype: string
	- name: utt
	dtype: string
	- name: annot_utt
	dtype: string
	- name: worker_id
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	- name: slot_method
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	- name: method
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	- name: judgments
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	- name: spelling_score
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	- name: language_identification
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	- name: tokens
	sequence: string
	- name: labels
	sequence: string
	- name: audio
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	audio:
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	- name: path
	dtype: string
	- name: is_transcript_reported
	dtype: bool
	- name: is_validated
	dtype: bool
	- name: speaker_id
	dtype: string
	- name: speaker_sex
	dtype: string
	- name: speaker_age
	dtype: string
	- name: speaker_ethnicity_simple
	dtype: string
	- name: speaker_country_of_birth
	dtype: string
	- name: speaker_country_of_residence
	dtype: string
	- name: speaker_nationality
	dtype: string
	- name: speaker_first_language
	dtype: string
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	- name: validation
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	num_examples: 2033
	- name: train
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	num_examples: 11514
	download_size: 9122884630
	dataset_size: 5223669968.0
	- config_name: es-ES
	features:
	- name: id
	dtype: string
	- name: locale
	dtype: string
	- name: partition
	dtype: string
	- name: scenario
	dtype:
	class_label:
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	'1': transport
	'2': calendar
	'3': play
	'4': news
	'5': datetime
	'6': recommendation
	'7': email
	'8': iot
	'9': general
	'10': audio
	'11': lists
	'12': qa
	'13': cooking
	'14': takeaway
	'15': music
	'16': alarm
	'17': weather
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	dtype: string
	- name: intent_idx
	dtype:
	class_label:
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	'1': iot_hue_lightchange
	'2': transport_ticket
	'3': takeaway_query
	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
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	'42': transport_query
	'43': music_likeness
	'44': email_query
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	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
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	- name: speaker_age
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	- name: speaker_ethnicity_simple
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	- name: speaker_country_of_birth
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	- name: speaker_country_of_residence
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	- name: speaker_nationality
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	- name: speaker_first_language
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	- name: validation
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	- config_name: fr-FR
	features:
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	- name: locale
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	'2': transport_ticket
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	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
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	'13': weather_query
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	'16': takeaway_order
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	'26': qa_definition
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	'29': audio_volume_other
	'30': calendar_remove
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	'33': email_sendemail
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	'36': play_radio
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	'38': datetime_convert
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	'57': music_query
	'58': play_podcasts
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	- config_name: hu-HU
	features:
	- name: id
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	- name: locale
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	- name: partition
	dtype: string
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	'13': cooking
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	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
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	'19': recommendation_locations
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	'38': datetime_convert
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	'2': transport_ticket
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	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
	'40': iot_hue_lightoff
	'41': iot_hue_lighton
	'42': transport_query
	'43': music_likeness
	'44': email_query
	'45': play_music
	'46': audio_volume_mute
	'47': social_post
	'48': alarm_set
	'49': qa_factoid
	'50': calendar_set
	'51': play_game
	'52': alarm_remove
	'53': lists_remove
	'54': transport_taxi
	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
	- name: intent_str
	dtype: string
	- name: utt
	dtype: string
	- name: annot_utt
	dtype: string
	- name: worker_id
	dtype: string
	- name: slot_method
	sequence:
	- name: slot
	dtype: string
	- name: method
	dtype: string
	- name: judgments
	sequence:
	- name: worker_id
	dtype: string
	- name: intent_score
	dtype: int8
	- name: slots_score
	dtype: int8
	- name: grammar_score
	dtype: int8
	- name: spelling_score
	dtype: int8
	- name: language_identification
	dtype: string
	- name: tokens
	sequence: string
	- name: labels
	sequence: string
	- name: audio
	dtype:
	audio:
	sampling_rate: 16000
	- name: path
	dtype: string
	- name: is_transcript_reported
	dtype: bool
	- name: is_validated
	dtype: bool
	- name: speaker_id
	dtype: string
	- name: speaker_sex
	dtype: string
	- name: speaker_age
	dtype: string
	- name: speaker_ethnicity_simple
	dtype: string
	- name: speaker_country_of_birth
	dtype: string
	- name: speaker_country_of_residence
	dtype: string
	- name: speaker_nationality
	dtype: string
	- name: speaker_first_language
	dtype: string
	splits:
	- name: train_115
	num_bytes: 40817549.0
	num_examples: 115
	- name: validation
	num_bytes: 750493456.0
	num_examples: 2033
	download_size: 1441835987
	dataset_size: 791311005.0
	- config_name: vi-VN
	features:
	- name: id
	dtype: string
	- name: locale
	dtype: string
	- name: partition
	dtype: string
	- name: scenario
	dtype:
	class_label:
	names:
	'0': social
	'1': transport
	'2': calendar
	'3': play
	'4': news
	'5': datetime
	'6': recommendation
	'7': email
	'8': iot
	'9': general
	'10': audio
	'11': lists
	'12': qa
	'13': cooking
	'14': takeaway
	'15': music
	'16': alarm
	'17': weather
	- name: scenario_str
	dtype: string
	- name: intent_idx
	dtype:
	class_label:
	names:
	'0': datetime_query
	'1': iot_hue_lightchange
	'2': transport_ticket
	'3': takeaway_query
	'4': qa_stock
	'5': general_greet
	'6': recommendation_events
	'7': music_dislikeness
	'8': iot_wemo_off
	'9': cooking_recipe
	'10': qa_currency
	'11': transport_traffic
	'12': general_quirky
	'13': weather_query
	'14': audio_volume_up
	'15': email_addcontact
	'16': takeaway_order
	'17': email_querycontact
	'18': iot_hue_lightup
	'19': recommendation_locations
	'20': play_audiobook
	'21': lists_createoradd
	'22': news_query
	'23': alarm_query
	'24': iot_wemo_on
	'25': general_joke
	'26': qa_definition
	'27': social_query
	'28': music_settings
	'29': audio_volume_other
	'30': calendar_remove
	'31': iot_hue_lightdim
	'32': calendar_query
	'33': email_sendemail
	'34': iot_cleaning
	'35': audio_volume_down
	'36': play_radio
	'37': cooking_query
	'38': datetime_convert
	'39': qa_maths
	'40': iot_hue_lightoff
	'41': iot_hue_lighton
	'42': transport_query
	'43': music_likeness
	'44': email_query
	'45': play_music
	'46': audio_volume_mute
	'47': social_post
	'48': alarm_set
	'49': qa_factoid
	'50': calendar_set
	'51': play_game
	'52': alarm_remove
	'53': lists_remove
	'54': transport_taxi
	'55': recommendation_movies
	'56': iot_coffee
	'57': music_query
	'58': play_podcasts
	'59': lists_query
	- name: intent_str
	dtype: string
	- name: utt
	dtype: string
	- name: annot_utt
	dtype: string
	- name: worker_id
	dtype: string
	- name: slot_method
	sequence:
	- name: slot
	dtype: string
	- name: method
	dtype: string
	- name: judgments
	sequence:
	- name: worker_id
	dtype: string
	- name: intent_score
	dtype: int8
	- name: slots_score
	dtype: int8
	- name: grammar_score
	dtype: int8
	- name: spelling_score
	dtype: int8
	- name: language_identification
	dtype: string
	- name: tokens
	sequence: string
	- name: labels
	sequence: string
	- name: audio
	dtype:
	audio:
	sampling_rate: 16000
	- name: path
	dtype: string
	- name: is_transcript_reported
	dtype: bool
	- name: is_validated
	dtype: bool
	- name: speaker_id
	dtype: string
	- name: speaker_sex
	dtype: string
	- name: speaker_age
	dtype: string
	- name: speaker_ethnicity_simple
	dtype: string
	- name: speaker_country_of_birth
	dtype: string
	- name: speaker_country_of_residence
	dtype: string
	- name: speaker_nationality
	dtype: string
	- name: speaker_first_language
	dtype: string
	splits:
	- name: train_115
	num_bytes: 39454913.0
	num_examples: 115
	- name: validation
	num_bytes: 726320851.0
	num_examples: 2033
	download_size: 1421726907
	dataset_size: 765775764.0
	configs:
	- config_name: all
	data_files:
	- split: train_115
	path: all/train_115-*
	- split: validation
	path: all/validation-*
	- split: train
	path: all/train-*
	- config_name: ar-SA
	data_files:
	- split: train_115
	path: ar-SA/train_115-*
	- split: validation
	path: ar-SA/validation-*
	- config_name: de-DE
	data_files:
	- split: train_115
	path: de-DE/train_115-*
	- split: validation
	path: de-DE/validation-*
	- split: train
	path: de-DE/train-*
	- config_name: es-ES
	data_files:
	- split: train_115
	path: es-ES/train_115-*
	- split: validation
	path: es-ES/validation-*
	- config_name: fr-FR
	data_files:
	- split: train_115
	path: fr-FR/train_115-*
	- split: validation
	path: fr-FR/validation-*
	- split: train
	path: fr-FR/train-*
	- config_name: hu-HU
	data_files:
	- split: train_115
	path: hu-HU/train_115-*
	- split: validation
	path: hu-HU/validation-*
	- config_name: ko-KR
	data_files:
	- split: train_115
	path: ko-KR/train_115-*
	- split: validation
	path: ko-KR/validation-*
	- config_name: nl-NL
	data_files:
	- split: train_115
	path: nl-NL/train_115-*
	- split: validation
	path: nl-NL/validation-*
	- config_name: pl-PL
	data_files:
	- split: train_115
	path: pl-PL/train_115-*
	- split: validation
	path: pl-PL/validation-*
	- config_name: pt-PT
	data_files:
	- split: train_115
	path: pt-PT/train_115-*
	- split: validation
	path: pt-PT/validation-*
	- config_name: ru-RU
	data_files:
	- split: train_115
	path: ru-RU/train_115-*
	- split: validation
	path: ru-RU/validation-*
	- config_name: tr-TR
	data_files:
	- split: train_115
	path: tr-TR/train_115-*
	- split: validation
	path: tr-TR/validation-*
	- config_name: vi-VN
	data_files:
	- split: train_115
	path: vi-VN/train_115-*
	- split: validation
	path: vi-VN/validation-*
	---

	# Speech-MASSIVE

	## Dataset Description
	Speech-MASSIVE is a multilingual Spoken Language Understanding (SLU) dataset comprising the speech counterpart for a portion of the [MASSIVE](https://aclanthology.org/2023.acl-long.235) textual corpus. Speech-MASSIVE covers 12 languages (Arabic, German, Spanish, French, Hungarian, Korean, Dutch, Polish, European Portuguese, Russian, Turkish, and Vietnamese) from different families and inherits from MASSIVE the annotations for the intent prediction and slot-filling tasks. MASSIVE utterances' labels span 18 domains, with 60 intents and 55 slots. Full train split is provided for French and German, and for all the 12 languages (including French and German), we provide few-shot train, validation, test splits. Few-shot train (115 examples) covers all 18 domains, 60 intents, and 55 slots (including empty slots).

	Our extension is prompted by the scarcity of massively multilingual SLU datasets and the growing need for versatile speech datasets to assess foundation models (LLMs, speech encoders) across diverse languages and tasks. To facilitate speech technology advancements, we release Speech-MASSIVE publicly available with [CC-BY-NC-SA-4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en).

	Speech-MASSIVE is accepted at INTERSPEECH 2024 (Kos, GREECE).


	## Dataset Summary
	- `validation`: validation split available for all the 12 languages
	- `test`: test split available for all the 12 languages
	- `train_115`: few-shot split available for all the 12 languages (all 115 samples are cross-lingually aligned)
	- `train`: train split available for French (fr-FR) and German (de-DE)

	\| lang \| split \| # sample \| # hrs \| total # spk </br>(Male/Female/Unidentified) \|
	\|:---:\|:---:\|:---:\|:---:\|:---:\|
	\| ar-SA \| validation \| 2033 \| 2.12 \| 36 (22/14/0) \|
	\| \| test \| 2974 \| 3.23 \| 37 (15/17/5) \|
	\| \| train_115 \| 115 \| 0.14 \| 8 (4/4/0) \|
	\| de-DE \| validation \| 2033 \| 2.33 \| 68 (35/32/1) \|
	\| \| test \| 2974 \| 3.41 \| 82 (36/36/10) \|
	\| \| train \| 11514 \| 12.61 \| 117 (50/63/4) \|
	\| \| train_115 \| 115 \| 0.15 \| 7 (3/4/0) \|
	\| es-ES \| validation \| 2033 \| 2.53 \| 109 (51/53/5) \|
	\| \| test \| 2974 \| 3.61 \| 85 (37/33/15) \|
	\| \| train_115 \| 115 \| 0.13 \| 7 (3/4/0) \|
	\| fr-FR \| validation \| 2033 \| 2.20 \| 55 (26/26/3) \|
	\| \| test \| 2974 \| 2.65 \| 75 (31/35/9) \|
	\| \| train \| 11514 \| 12.42 \| 103 (50/52/1) \|
	\| \| train_115 \| 115 \| 0.12 \| 103 (50/52/1) \|
	\| hu-HU \| validation \| 2033 \| 2.27 \| 69 (33/33/3) \|
	\| \| test \| 2974 \| 3.30 \| 55 (25/24/6) \|
	\| \| train_115 \| 115 \| 0.12 \| 8 (3/4/1) \|
	\| ko-KR \| validation \| 2033 \| 2.12 \| 21 (8/13/0) \|
	\| \| test \| 2974 \| 2.66 \| 31 (10/18/3) \|
	\| \| train_115 \| 115 \| 0.14 \| 8 (4/4/0) \|
	\| nl-NL \| validation \| 2033 \| 2.14 \| 37 (17/19/1) \|
	\| \| test \| 2974 \| 3.30 \| 100 (48/49/3) \|
	\| \| train_115 \| 115 \| 0.12 \| 7 (3/4/0) \|
	\| pl-PL \| validation \| 2033 \| 2.24 \| 105 (50/52/3) \|
	\| \| test \| 2974 \| 3.21 \| 151 (73/71/7) \|
	\| \| train_115 \| 115 \| 0.10 \| 7 (3/4/0) \|
	\| pt-PT \| validation \| 2033 \| 2.20 \| 107 (51/53/3) \|
	\| \| test \| 2974 \| 3.25 \| 102 (48/50/4) \|
	\| \| train_115 \| 115 \| 0.12 \| 8 (4/4/0) \|
	\| ru-RU \| validation \| 2033 \| 2.25 \| 40 (7/31/2) \|
	\| \| test \| 2974 \| 3.44 \| 51 (25/23/3) \|
	\| \| train_115 \| 115 \| 0.12 \| 7 (3/4/0) \|
	\| tr-TR \| validation \| 2033 \| 2.17 \| 71 (36/34/1) \|
	\| \| test \| 2974 \| 3.00 \| 42 (17/18/7) \|
	\| \| train_115 \| 115 \| 0.11 \| 6 (3/3/0) \|
	\| vi-VN \| validation \| 2033 \| 2.10 \| 28 (13/14/1) \|
	\| \| test \| 2974 \| 3.23 \| 30 (11/14/5) \|
	\|\| train_115 \| 115 \| 0.11 \| 7 (2/4/1) \|


	## How to use

	### How to use

	The `datasets` library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the `load_dataset` function.

	For example, to download the French config, simply specify the corresponding language config name (i.e., "fr-FR" for French):

	```python
	from datasets import load_dataset

	speech_massive_fr_train = load_dataset("FBK-MT/Speech-MASSIVE", "fr-FR", split="train")
	```

	In case you don't have enough space in the machine, you can stream dataset by adding a `streaming=True` argument to the `load_dataset` function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.
	```python
	from datasets import load_dataset

	speech_massive_de_train = load_dataset("FBK-MT/Speech-MASSIVE", "de-DE", split="train", streaming=True)
	list(speech_massive_de_train.take(2))
	```

	You can also load all the available languages and splits at once.
	And then access each split.
	```python
	from datasets import load_dataset

	speech_massive = load_dataset("FBK-MT/Speech-MASSIVE", "all")
	multilingual_validation = speech_massive['validation']
	```

	Or you can load dataset's all the splits per language to separate languages more easily.
	```python
	from datasets import load_dataset, interleave_datasets, concatenate_datasets

	# creating full train set by interleaving between German and French
	speech_massive_de = load_dataset("FBK-MT/Speech-MASSIVE", "de-DE")
	speech_massive_fr = load_dataset("FBK-MT/Speech-MASSIVE", "fr-FR")
	speech_massive_train_de_fr = interleave_datasets([speech_massive_de['train'], speech_massive_fr['train']])

	# creating train_115 few-shot set by concatenating Korean and Russian
	speech_massive_ko = load_dataset("FBK-MT/Speech-MASSIVE", "ko-KR")
	speech_massive_ru = load_dataset("FBK-MT/Speech-MASSIVE", "ru-RU")
	speech_massive_train_115_ko_ru = concatenate_datasets([speech_massive_ko['train_115'], speech_massive_ru['train_115']])
	```

	## Dataset Structure

	### Data configs
	- `all`: load all the 12 languages in one single dataset instance
	- `lang`: load only `lang` in the dataset instance, by specifying one of below languages
	- ```ar-SA, de-DE, es-ES, fr-FR, hu-HU, ko-KR, nl-NL, pl-PL, pt-PT, ru-RU, tr-TR, vi-VN```

	### Data Splits
	- `validation`: validation(dev) split available for all the 12 languages
	- `train_115`: few-shot (115 samples) split available for all the 12 languages
	- `train`: train split available for French (fr-FR) and German (de-DE)

	> [!WARNING]
	> `test` split is uploaded as a separate dataset on HF to prevent possible data contamination
	- ⚠️ `test`: available _only_ in the separate HF dataset repository. ⚠️
	- [https://huggingface.co/datasets/FBK-MT/Speech-MASSIVE-test](https://huggingface.co/datasets/FBK-MT/Speech-MASSIVE-test)

	### Data Instances

	```json
	{
	// Start of the data collected in Speech-MASSIVE
	'audio': {
	'path': 'train/2b12a21ca64a729ccdabbde76a8f8d56.wav',
	'array': array([-7.80913979e-...7259e-03]),
	'sampling_rate': 16000},
	'path': '/path/to/wav/file.wav',
	'is_transcript_reported': False,
	'is_validated': True,
	'speaker_id': '60fcc09cb546eee814672f44',
	'speaker_sex': 'Female',
	'speaker_age': '25',
	'speaker_ethnicity_simple': 'White',
	'speaker_country_of_birth': 'France',
	'speaker_country_of_residence': 'Ireland',
	'speaker_nationality': 'France',
	'speaker_first_language': 'French',
	// End of the data collected in Speech-MASSIVE

	// Start of the data extracted from MASSIVE
	// (https://huggingface.co/datasets/AmazonScience/massive/blob/main/README.md#data-instances)
	'id': '7509',
	'locale': 'fr-FR',
	'partition': 'train',
	'scenario': 2,
	'scenario_str': 'calendar',
	'intent_idx': 32,
	'intent_str': 'calendar_query',
	'utt': 'après les cours de natation quoi d autre sur mon calendrier mardi',
	'annot_utt': 'après les cours de natation quoi d autre sur mon calendrier [date : mardi]',
	'worker_id': '22',
	'slot_method': {'slot': ['date'], 'method': ['translation']},
	'judgments': {
	'worker_id': ['22', '19', '0'],
	'intent_score': [1, 2, 1],
	'slots_score': [1, 1, 1],
	'grammar_score': [4, 4, 4],
	'spelling_score': [2, 1, 2],
	'language_identification': ['target', 'target', 'target']
	},
	'tokens': ['après', 'les', 'cours', 'de', 'natation', 'quoi', 'd', 'autre', 'sur', 'mon', 'calendrier', 'mardi'],
	'labels': ['Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'Other', 'date'],
	// End of the data extracted from MASSIVE
	}
	```
	### Data Fields

	`audio.path`: Original audio file name

	`audio.array`: Read audio file with the sampling rate of 16,000

	`audio.sampling_rate`: Sampling rate

	`path`: Original audio file full path

	`is_transcript_reported`: Whether the transcript is reported as 'syntatically wrong' by crowd-source worker

	`is_validated`: Whether the recorded audio has been validated to check if the audio matches transcript exactly by crowd-source worker

	`speaker_id`: Unique hash id of the crowd source speaker

	`speaker_sex`: Speaker's sex information provided by the crowd-source platform ([Prolific](http://prolific.com))
	- Male
	- Female
	- Unidentified : Information not available from Prolific

	`speaker_age`: Speaker's age information provided by Prolific
	- age value (`str`)
	- Unidentified : Information not available from Prolific

	`speaker_ethnicity_simple`: Speaker's ethnicity information provided by Prolific
	- ethnicity value (`str`)
	- Unidentified : Information not available from Prolific

	`speaker_country_of_birth`: Speaker's country of birth information provided by Prolific
	- country value (`str`)
	- Unidentified : Information not available from Prolific

	`speaker_country_of_residence`: Speaker's country of residence information provided by Prolific
	- country value (`str`)
	- Unidentified : Information not available from Prolific

	`speaker_nationality`: Speaker's nationality information provided by Prolific
	- nationality value (`str`)
	- Unidentified : Information not available from Prolific

	`speaker_first_language`: Speaker's first language information provided by Prolific
	- language value (`str`)
	- Unidentified : Information not available from Prolific


	### Limitations

	As Speech-MASSIVE is constructed based on the MASSIVE dataset, it inherently retains certain grammatical errors present in the original MASSIVE text. Correcting these errors was outside the scope of our project. However, by providing the `is_transcripted_reported` attribute in Speech-MASSIVE, we enable users of the dataset to be aware of these errors.


	## License

	All datasets are licensed under the [CC-BY-NC-SA-4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en).

	### Citation Information

	You can access the Speech-MASSIVE paper at [link to be added](https://arxiv.com).
	Please cite the paper when referencing the Speech-MASSIVE corpus as:

	```
	Citation to be added
	```