Omkar2118/datasets huggingface dataset:
CASA
Full name: Clinical annotations for automatic Stuttering Assessment

## Annotation Guidlines

Three speech and language pathologists, with experience ranging from 2 to 40 years, independently annotated and analyzed the audiovisual samples sourced from the [Fluencybank](https://talkbank.org/fluency/) Adults Who Stutter(AWS) dataset. The annotations were created using the [ELAN](https://archive.mpi.nl/tla/elan/) tool. 

For **boundary Annotations**, the annotators marked the onset and offset of each stuttering instance by dragging the mouse from the beginning to the end of the event, following the recommendations from the book TOCS: Test of childhood stuttering by Gillam et al. (2009). Specifically: (1) for repetitions, the stuttering onset is the point where the repeated speech begins, and the offset is where fluent speech resumes; (2) for prolongations or blocks, the onset is the start of the disfluent speech sound, with the offset marked by the next fluent sound.


After identifying each stuttering moment, the annotators classified the **disfluency type** based on the LBDL taxonomy, secondary behaviors using Riley’s (2009) SSI-4 classification, and the tension level according to a 0-3 scale, as proposed by the article Characteristics of stuttering-like disfluencies in Dutch-speaking children by [Boey et al](https://doi.org/10.1016/j.jfludis.2007.07.003).

The annotations are categorized into 3 broad groups
### Core
1. **SR:** Syllable Repetition, indicating repeated movement of an entire syllable;
2. **ISR:** Incomplete Syllable Repetition, repetition of parts of syllables;
3. **MUR:** Multisyllable Unit Repetition, repetitions involving multiple syllables;
4. **P:** sound Prolongation; and
5. **B:** Blocks.

### Secondary
1. **V:** Verbal behaviors, including noisy breathing, whistling, sniffing, blowing, or clicking sounds;  
2. **FG:** Facial Grimaces, such as jaw jerking, tongue protrusion, lip pressing, jaw muscle tension, or eye movements;  
3. **HM:** Head Movements, including backward, forward, or turning motions; and  
4. **ME:** Movements of Extremities, such as arm and hand gestures, torso movements, or leg motions.

### Tension levels 
- 0 – no tension
- 1 – mild, subtle physical tension
- 2 – moderate tension, noticeable and distracting
- 3 – severe tension, highly distracting and produced with considerable effort

##

Introducing paper: Clinical Annotations for Automatic Stuttering Severity Assessment
ArVoice
Full name: ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis

We introduce ArVoice, a multi-speaker Modern Standard Arabic (MSA) speech corpus with diacritized transcriptions, intended for multi-speaker speech synthesis, and can be useful for other tasks such as speech-based diacritic restoration, voice conversion, and deepfake detection. 

ArVoice comprises:
 (1) a new professionally recorded set from six voice talents with diverse demographics, 
 (2) a modified subset of the Arabic Speech Corpus; and 
 (3) high-quality synthetic speech from two commercial systems. 

The complete corpus consists of a total of 83.52 hours of speech across 11 voices; around 10 hours consist of human voices from 7 speakers. We train three open-source TTS and two voice conversion systems to illustrate the use cases of the dataset. The corpus is available for research use.

Introducing paper: ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis
monkey doo

the dataset is a monkey doo doo dataset

Introducing paper: 100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models