---
title: "Italian Speech Recognition Dataset"
description: "The dataset provides 10+ hours of annotated telephone dialogues from 20+ native speakers in Italy, delivering high-quality audio recordings, transcriptions, and speaker metadata to support…"
url: "https://unidata.pro/datasets/italian-speech-recognition-dataset/"
date_modified: "2025-12-11T15:32:32+03:00"
language: "en-US"
---
The dataset provides 10+ hours of annotated telephone dialogues from 20+ native speakers in Italy, delivering high-quality audio recordings, transcriptions, and speaker metadata to support speech recognition systems, NLP training, and machine learning models with diverse Italian speech datasets

## Dataset Structure

### The Numbers Section

**Numbered list:**

- **Number:** 10+ — **Text:** Hours
- **Number:** 20+ — **Text:** Speakers

### Tooltips Section

**Tooltip items:**

- **Name:** NLP
- **Name:** LLM
- **Name:** Machine Learning
- **Name:** Audio Processing
- **Name:** ASR
- **Name:** Voice Recognition

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Audio of telephone dialogues in Italian for training NLP models in real-world conversational scenarios. |
| Data types | Audio |
| Tasks | Speech recognition, NLP |
| Country | Italy(ITA) |
| Hours of telephone dialogue | 10 |
| Number of speakers | 20 |
| Labeling | Annotation (ID, Language, Format, Minutes) |
| Recording device | Telephone |

**Media Slider:** - **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/03/italian-speech-recognition-dataset.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1LsTdoqdYkSya6bRsVsZhvxYhRHjTdia8?usp=sharing)

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Audio Format | WAW, M4A, MP3 |
| Duration | Mean =11 min |
| Recording condition | Low background noise (indoor) |

**Source and data collection methodology:** Source and collection methodology: Data was collected via crowdsourcing platforms

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Call Centers & Customer Service — **Title:** Improving Italian Telephone Dialogue Recognition — **Text:** Italian Speech Recognition Dataset includes authentic audio recordings of real conversations. Speech samples from native Italian speakers help call centers train recognition systems for spoken Italian. Companies use it to enhance automatic speech recognition, improve audio transcriptions, and provide better customer support across Italian-speaking markets.
- **Industry:** AI & Machine Learning Research — **Title:** Developing Recognition Models with Training Data — **Text:** This speech recognition dataset offers high-quality training data for machine learning and learning models. The dataset comprises audio files and accurate transcriptions from diverse speech types. Researchers use it to train recognition models and speech technology with high accuracy, supporting advanced speech processing and language processing applications.
- **Industry:** Multilingual & Cross-Language Applications — **Title:** Supporting Translation and Natural Language Processing — **Text:** The dataset is used in multilingual speech projects, where it is combined with other languages for speech translation and speech synthesis. Its audio samples from native speakers enrich multilingual datasets, ensuring recognition systems adapt well in cross-lingual conversational AI. Developers use it to refine language processing tools for global platforms.
- **Industry:** Academic & Commercial Use — **Title:** Linguistic Research and Speech Technology Deployment — **Text:** The dataset is applied in linguistic research, studying linguistic features of spoken language and speech emotion. Businesses also use it in speech technology for assistants, transcription platforms, and emotion recognition systems. Since the datasets offer high-quality audio, they support accurate transcriptions and reliable real-world speech recognition solutions.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** How was the data collected? — **Answer:** The data was recorded on standard telephone devices under controlled indoor conditions with low background noise. This ensures clean audio recordings suitable for speech technology and recognition systems.
- **Question:** Can I request a sample of Italian Speech Recognition Dataset before purchasing or downloading it? — **Answer:** Yes, a sample of the dataset can be provided. This allows you to evaluate audio recordings, transcriptions, and speaker metadata before committing to the full dataset.
- **Question:** Is it possible to request a custom dataset? — **Answer:** Yes, Unidata can create custom datasets to fit your project needs. You may request additional dialects of spoken Italian, specific speaker demographics, or unique recording conditions to improve the performance of your recognition models.
- **Question:** How are Unidata datasets licensed? — **Answer:** Unidata datasets follow a dual-licensing model. Free speech samples are offered for testing, while the full Italian speech recognition dataset is available only for purchase.
- **Question:** How are Unidata datasets stored? — **Answer:** Unidata stores all datasets on AWS cloud infrastructure, which guarantees secure, scalable, and reliable storage. The system follows ISO 27001 and ISO 27701 standards, ensuring high-quality audio management for automatic speech recognition, speech processing, and conversational AI research.
- **Question:** How long does it take to receive the dataset? — **Answer:** After submitting a request, Unidata will contact you to finalize the details and required documentation. Once the agreement is signed and payment confirmed, Italian Speech Recognition Dataset will be delivered within 3-10 business days.
- **Question:** Is this a real-world dataset or synthetic data? — **Answer:** This is a real-world dataset. The dataset contains spoken Italian captured in controlled conditions with low background noise. It does not include synthetic data and is ideal for speech recognition, emotion detection, and natural language processing tasks.
- **Question:** Why is natural Italian dialogue important for training speech recognition models? — **Answer:** Natural dialogue contains real communication patterns, including different speaking styles, sentence structures, and conversational contexts. Training with realistic speech data helps models perform better when processing everyday Italian conversations.

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