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Corpus has data from various modes of communication, including speech, gestures, and facial expressions. It was created at the University of Nottingham, United Kingdom, and serves as a valuable resource for studying human communication.

The NMMC was developed in the early 2000s by researchers at the University of Nottingham's School of Psychology.

It's a multimodal corpus.

NMMC has about 250.000 words.

The primary purpose of the Nottingham Multi-Modal Corpus is to facilitate research in various fields, including psychology, linguistics, human-computer interaction, and communication studies.

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Corpus (NMMC)

This corpus was made at the University of Nottingham.

The purpose of creating the Nottingham Multi-Modal Corpus (NMMC) was to investigate and understand language patterns in multi-modal communication. Researchers aimed to analyze how language is used in various contexts, encompassing not only text but also images and possibly audio. The corpus serves as a valuable resource for linguistic research.

About characteristics:

• Representative: NMMC is designed to capture language in various real-world situations, ensuring a diverse representation of communication.

• Balanced: The corpus includes a mix of different modes (text, images, audio) to provide a well-rounded view of multi-modal language use.

• Size: The size of the NMMC, though not specified, would likely contribute to its richness in data, facilitating in-depth linguistic research.

The Nottingham Multi-Modal Corpus (NMMC) is a multi-modal corpus. This means it includes various types of data, such as text, images, and possibly audio.

Where we can use it:

Linguistic Research:

• Researchers can analyze language patterns across different modes (text, images, audio), gaining insights into how people communicate in diverse settings.

• Enables the study of language variation and use in real-world, multi-modal communication.

2. Technology Development:

• Provides a rich dataset for training and testing language-related algorithms and models.

3. Human-Computer Interaction (HCI):

• Facilitates the understanding of how language is used in conjunction with other modalities, enhancing the design of more effective and intuitive human-computer interfaces.

• Supports research in improving communication between humans and technology.

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The MICASE corpus is a spoken language corpus of approximately 1.7 million words (nearly 200 hours) focusing on contemporary university speech within the microcosm of the University of Michigan, in Ann Arbor, Michigan. This is a typical large public research university with about 37,000 students, approximately one-third of whom are

graduate students. Speakers represented in the corpus include faculty, staff, and all levels of students, and native, near-native and non-native speakers.

Time of compilation: 1997-2002.

Genres:

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1. The remaining 10% of the BNC is samples of spoken language use. These are presented and recorded in the form of orthographic transcriptions.

The spoken corpus consists of 2 parts: demographic, containing the transcriptions of spontaneous natural and conversations produced by volunteers of various age groups, social classes and originating from different regions.

2. The other part involves context-governed samples such as transcriptions of recordings made at specific types of meeting and event. The majority of the recordings are freely available from the Oxford University Phonetics Laboratory.

3. The spoken part is made up of :

50% transcriptions of natural spontaneous conversations

124 volunteers living in 38 locations across the UK recorded all their conversations for 2-3 days.

There were equal numbers of men and women, approximately equal numbers from each age group and equal numbers from each of four social groupings.

50% transcriptions of recordings made at four specific types of meeting or event:

Educational and informative events (lectures, news broadcasts, tutorials)

Institutional and public events (sermons, political speeches, council meetings, parliamentary proceedings)

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Hong Kong Corpus of Spoken English (HKCSE)

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Hong Kong Corpus of Spoken English (HKCSE)

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The HKCSE is a large and balanced corpus, with currently 907,657 words.

The HKCSE was created by Winnie Cheng, Chris Greaves, and Martin Warren from the Research Centre for Professional Communication in English of the Hong Kong Polytechnic University.

The purpose of creating this corpus was to represent spoken English in Hong Kong in four areas: academic, business, conversation, and public.

The corpus also has a prosodic version, which includes information on intonation, stress, and pauses.

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The Cambridge Learner Corpus (CLC) is a collection of exam scripts written by students learning English.

The Cambridge and Nottingham Corpus of Discourse in English (CANCODE) forms a part of the Cambridge International Corpus (CIC).

Characteristics:

1. Size - 5 million words

2. Representativeness: representative of spoken British English used in everyday situations.

3. CANCODE is a static corpus, meaning it doesn't include new recordings. It reflects spoken English from the period between 1995 and 2000.

4. Authenticity: known for its focus on authenticity. The recordings are of spontaneous speech, not staged or scripted interactions.

5. Sample: Data have been recorded in a wide variety of situations: casual conversation, people working together, people shopping, people finding out information, discussions, etc.

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Scottish Corpus of Texts & Speech (SCOTS) is a valuable resource for anyone interested in the modern Scottish language.

1. Origins & Creators:

- Developed by the University of Glasgow and the University of Edinburgh.

- Funded by the Arts and Humanities Research Council (AHRC) from 2004 to 2010.

- Launched online in November 2004.

- Aimed to document and preserve the modern Scottish language.

2. Characteristics:

- Contains nearly 4.7 million words as of 2015.

- Multilingual, covering Scottish English, various Scots dialects, and Scottish Gaelic.

- Comprises 60% written text and 40% spoken text, with audio for spoken content.

- Features diverse text types: formal, informal, news articles, fiction, etc.

- Synchronic corpus focused on contemporary Scottish language use from the 1940s onwards.

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A corpus of Scottish tests and speeches (SCOTS)

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A corpus of Scottish tests and speeches (SCOTS)

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Augmented Multi-Party Interaction Corpus (AMI)

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Augmented Multi-Party Interaction Corpus (AMI)

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Michigan Corpus of Academic Spoken English (MICASE)

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Michigan Corpus of Academic Spoken English (MICASE)

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Hong Kong Corpus of Spoken English (HKCSE)

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Hong Kong Corpus of Spoken English (HKCSE)

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Limerick Corpus of Irish English (LCIE).

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Limerick Corpus of Irish English (LCIE).

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Cambridge and Nottingham Corpus of Discourse in English (CANCODE).

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Cambridge and Nottingham Corpus of Discourse in English (CANCODE).