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Home > All Category Datasets > Speech Recognition Datasets > 310 Hours Swahili Speech Dataset for ASR and AI Model Training

310 Hours Swahili Speech Dataset for ASR and AI Model Training

Tanzania speech data
Swahili audio corpus
African language dataset
multilingual ASR data
low-resource language speech corpus
voice AI dataset
Swahili speech dataset

This dataset contains 310 hours of Swahili speech recordings collected from native Tanzanian speakers through topic-based dialogue conversations. The dataset includes accurate transcriptions and comprehensive speaker metadata, including speaker ID, gender, age, and other attributes. Our dataset was collected from extensive and diversify speakers, geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

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SpecificationsSpecifications
Format
24kHz, 16 bit, wav, mono channel;
Content category
Dialogue based on given topics;
Recording condition
Low background noise (indoor);
Recording device
Android smartphone, iPhone;
Speaker
About 300 native speakers in total;
Country
Tanzania(TZA);
Language(Region) Code
sw-TZ;
Language
Swahili;
Features of annotation
Transcription text, timestamp, speaker ID, gender, noise,PII redacted.
Accuracy Rate
Word Accuracy Rate (WAR) 98%
Sample Sample
  • Audio

    Mmmh kwangu mimi napenda wali na njegele, [N]

  • Audio

    sababu ni chakula kinachonivutia na kinachoongeza madini mwilini.

  • Audio

    Ya hayo madini ambayo unazungumzia wewe.

  • Audio

    Kwamba yanaongeza inaongeza afya mwilini pamoja na madini.

  • Audio

    Lakini pia mimi napokula ugali na dagaa, ni chakula ambacho kinanifanya nijisikie nimeshiba. [N]

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What languages and scenarios are covered by Nexdata’s speech recognition datasets?

Nexdata offers speech recognition datasets covering a broad range of languages, dialects, and accents, backed by extensive global language resources. Our datasets include diverse speakers, acoustic environments, and real-world speech scenarios, supporting multilingual ASR, voice assistants, conversational AI, speech-to-text, and other speech-enabled applications.

Can Nexdata customize speech recognition datasets for specific languages or requirements?

Yes. If our off-the-shelf datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, transcription, and annotation services. We can customize datasets based on target languages or dialects, speaker profiles, recording environments, speech scenarios, data volume, and annotation specifications to meet specific ASR development needs.

How does Nexdata ensure the quality and scalability of speech recognition datasets?

Nexdata applies multi-stage quality control throughout speech data collection, transcription, annotation, and validation. Combined with our extensive language resources and scalable collection capabilities, we can support both large-scale multilingual projects and specialized datasets for specific languages, dialects, accents, and speech scenarios.

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