Update READM.md

README.md

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     path: data/train-*
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+# Dataset Card for AMI_annotation
+
+## Dataset Details
+
+### Dataset Description
+**AMI_annotation** is a structurally parsed and annotated multi-modal meeting corpus derived from the AMI Meeting Corpus manual annotations. It features detailed meeting-level metadata, abstractive meeting summaries, individual participant summaries mapped by roles/speakers, segmented timestamps, speaker-specific text transcriptions, integrated Named Entity Recognition (NER), and discussion topic vectors.
+
+- **Curated by:** Rabindra Nath Nandi
+- **Language(s) (NLP):** English
+- **License:** [More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+Each row in the dataset represents a unique meeting instance indexed by its `meeting_id`. 
+
+### Data Fields
+* `meeting_id` (string): Unique identifier for the meeting session (e.g., `ES2002a`).
+* `abstractive` (struct): Meeting-level abstractive summaries containing:
+  * `abstract` (list of strings): High-level meeting summary sentences.
+  * `actions` (list of strings): Stated action items and directives.
+  * `decisions` (list of strings): Concluded decisions made by the team.
+  * `problems` (list of strings): Open issues or problems discussed.
+* `participants_summary` (struct): Role-specific summaries for participants (`A`, `B`, `C`, `D`), tracking individual perspectives on abstract, actions, decisions, and problems.
+* `topics` (list of strings): Chronological meeting agenda and discussion topics.
+* `key_speakers` (list): Speaker profile records containing:
+  * `speaker_id` (string): Identifier code for the speaker.
+  * `speech` (string): Consolidated full-text monologue or contributions.
+  * `name_entities` (list): Extracted entities mapped to types (`text`, `type`).
+* `utterance` (list): Time-aligned utterance blocks containing:
+  * `speaker` (string): Speaker label.
+  * `start_time` (float64): Utterance start timestamp in seconds.
+  * `end_time` (float64): Utterance end timestamp in seconds.
+  * `text` (string): Transcribed text segment.
+
+## Uses
+
+### Direct Use
+Designed for training and evaluating Audio Large Language Models (AudioLLMs), automatic meeting summarization, multi-party dialogue analysis, and named entity recognition tasks.
+
+## Dataset Creation
+
+### Curation Rationale
+Processed using automated XML parsers to structure legacy AMI corpus annotations into clean, standardized JSON table rows compatible with the Hugging Face `datasets` ecosystem.
+
+## Bias, Risks, and Limitations
+Corpus reflects natural multi-party meeting dynamics, containing colloquial speech patterns, interruptions, and subjective participant summaries.