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Datasets:
ghananlpcommunity
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twi-speech-text-multispeaker-16k

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audioduration (s)
0.04
10
text
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Wɔbɛtumi akɔ dan a ɛtoa wɔn so no ne ne yɔnko a wadi mfeɛ akɔyɛ adidi kronkron no?
7.02
Honhom no ate wɔn ho ama wɔn nnipadua no ayɛ afoforɔ.
3.82
Saa kɛseyɛ no ba nkakrankakra.
3.42
mɛbɔ mpaeɛ ma Adwurade ama mahunu deɛ Ɔpɛ ma onipa no,
4.34
Mehunuu sɛ wɔn mu pii resu.
3.22
mɛkasa akyerɛ mo a mopɛsɛ mode mo asɔfodie no yɛ adwuma yie wɔ mo ankasa mo som mu.
6.72
mmom mehwɛɛ mpanyinfoɔ yi mu biara anim.
3.54
Masua sɛ wei ne ɔsom safoa na yɛahyira afoforɔ wɔ Ne din mu.
6.28
Wɔbɛsiesie Awurade nkorɔfoɔ ama N’animuonyam Mmaeɛ a ɛtɔ so Mmienu no.
6.88
Nanso ebia ɛbɛyɛ mo nwanwa sɛdeɛ saa ɔfrɛ yi mo bɛyɛ no kɛse kyerɛ ma mo.
4.78
Sɛ me ne mo kasa na mete mo gyedie kɛseɛ no nka a,
4.94
Me gye dii sɛ m’asɔfodie asɛdeɛ ara ne sɛ mɛkyɛ adidi kronkron no wɔ me ankasa dan asa so.
8.14
Ɔde asɔfodie no hyɛɛ wo nsa,
1.7
na ɛwɔ sɛ ɔtena fie.
6
Wɔ nnawɔtwe pii mu no,
0.98
meda wo ase,
0.44
Nhwɛsoɔ,
0.46
na ɛwɔ statio mfonyin bi wɔ aseɛ.
3.84
Metee suahunu bi nnansa yi a ɛkaee me fa saa ɔdɔ yi ho.
4.64
na ɔkaa sɛ,
0.6
Wɔbɛboaboa Isreal ano.
7.08
Wɔn a wɔahyɛ wɔn elder afoforɔ no bɛpɛ sɛ wɔbɛtie.
4.3
Me nuanom adɔfoɔ,
1.26
mate nhyira a wɔde ama a ayɛ me ne deɛ ɔregye nhyira no nso nwanwa.
5.6
ne onuabaa a ɔsom no no tumi san kɔɔ asɔre.
3.58
Ɛyɛ adesua ma me sɛ mɛhwɛ m’akyi wɔ me berɛ a na meyɛ dikɔn no.
5.4
amen.
3.24
Wɔkaa sɛ menkyɛ adidi kronkron no.
3.7
ɛnyɛ sɛdeɛ mɛtumi ayɛ m’afa mu deɛ.
2.7
Maame baako sɔɔ me nsa,
3.14
a wɔde ama wɔ Ne din mu.
3.98
Berɛ a wɔtwee Asɔre nhyiamu nyinaa saneeɛ ɛnam COVID- nsanyadeɛ nti,
5.36
nanso ɛbɛba.
0.64
hwɛɛ soro,
0.42
Ɔpɛ a ɔwɔ sɛ ɔbɛyɛ sɔfodwuma anyini berɛ a ɔresom wɔ Awurade din mu wɔ n’ankasa ne kwan a ɔnim so.
5.58
onuabarima no,
0.76
Ɔnim wo ankasa,
0.72
Mekae sɛ na ɛyɛ Yalecrest Ward a ɛwɔ Salt Lake City,
6.3
mehunuu me ho wɔ wɔɔd kɛseɛ a dikɔnfoɔ pii wɔ mu.
3.68
Sɛ ɔhwɛfoɔ no,
1.04
Ɔhwɛfoɔ no maa kwan,
1.08
Sɛ mɛdwene kwan a mɛfa so anaa mɛyɛ no pɛpɛɛpɛ berɛ a merekyɛ adidi kronkron no,
6.8
awieɛ no yɛ adekorɔ.
0.6
Na asɔre no nyinaa hyia wɔ yɛn fie.
2.119
kɔyɛ Awurade adidi kronkron ma no wɔ ne fie.
2.76
Mennim sɛ onuabarima somfoɔ yi abɔ mpaeɛ,
1.3
Megye di sɛ yɛbɛtumi ama yɛn asɔfodie adwuma som no ayɛ kɛseɛ yɛn nkwa nna nyinaa mu na mpo atra akɔ akyiri.
6.4
Ɛyɛ den sɛ Awurade,
1.04
wɔ Ne din mu.
0.62
sɛdeɛ wɔn a ɔsom wɔn no bɛhunu Awurade dɔ no,
2.22
te sɛ me deɛ no wɔ ahwɛbeaeɛ hɔ no,
3.4
Asi pii berɛ a mama obi a ɔda owuo mpa so na abusuafoɔ atwa ne ho ahyia,
6.74
wɔsomaa me kɔsraa adidi kronkron nhyiamu wɔ ahwɛbeaɛ bi.
4.04
ayɔnkofoɔ asomfoɔ wɔ Onyankopɔn asɔfodie mu,
4.12
mehunuu sɛ dikɔnfoɔ no de pɛpɛyɛ na ɛnante kyekyɛ adidi kronkron no te sɛ deɛ wɔahyɛda atete wɔn.
8.46
Ɛyɛ me anisɔ saa berɛ yi sɛ saa da no,
3.32
meda wo ase.
0.48
ɔgyee penee,
0.68
Saa nsunsuansoɔ korɔ no ara ba berɛ a mɛbɔ mpaeɛ ansa na m’ahyira obi a ɔyare anaa ɔwɔ ahohia mu.
6.86
Ɛda adi pefee sɛ,
0.74
Nokorɛ mu,
0.52
ɛnam ahwɛyie dodoɔ nti,
1.02
Ɛbɛtumi ayɛ bɔkɔɔ,
1.24
sɛ ɔsɔfo panyin yi no,
0.86
n’abusua,
0.6
Mmom seesei mahunu sɛ kwan pa wɔ hɔ a yɛdebɔ mpaeɛ na yɛdwene wɔ berɛ a yɛrenyini wɔ asɔfodie som mu.
7.36
Ɛde mmɔdemmɔ na yɛde bɛhunu deɛ Awurade pɛ afiri deɛ yɛpɛ ne deɛ obi pɛ.
6.5
Berɛ a ɔfrɛɛ no sɛ ɔde adidi kronkron no bɛbrɛ no,
4.28
N’asɔfodie som,
0.86
Wɔ m’adidi kronkron nhyiamu a ɛdikan hɔ no,
2.74
ɔsomfoɔ barima yi bisaa ne hwɛfoɔ nnansa yi sɛ obi foforɔ bi wɔ hɔ a ɔbɛtumi asra no anaa.
8.16
Saa nkanyan korɔ no ba berɛ a agya panyinom kyene ɛkɔm na wɔbɔ mpaeɛ gye akwankyerɛ sɛ wɔde nhyira a Awurade no pɛ bɛma obi.
9.22
ne deɛ Onyankopɔn ayi wɔn.
1.68
Berɛ a ɔkɔduruu ne fie Kwasiada anɔpa no,
2.36
Asɔfodie kannifoɔ ma me ne menua no yɛ ɔhonufoɔ foforɔbi a afei na ɔno ankasa anya asɔfodie no.
8.341
mebɔ mpaeɛ sɛ mɛhunu nhyira a Awurade pɛ sɛ mede ma wɔ Ne din mu.
6.24
bɛtumi de atenetene ahyira obi.
3.32
Wɔ berɛ mu no,
7.8
Awurade na ɔseɛ.
1.46
Awurade bɛyi Ne pɛ no bebree adi akyerɛ Ne nkɔmhyɛfoɔ ne Ne nkoa.
6.44
Botaeɛ nti a wɔde asɔfodie no ma ne sɛ yɛbɛnya akwanya de ahyira nnipa ama Awurade,
5.9
Ɛbaa me nteaseɛ mu deɛ enti a wɔde asɔfodie no ma ankorɛankorɛ.
4.38
redi nkanyan biara ɔde bɛma me so a me ankasa nsusuiɛ nka ho.
7.7
Bio,
0.16
ɛyɛ animuoyamhyɛ ma me sɛ me ne mo rekasa anadwo yi.
3.74
Na ɔhwɛfoɔ bi a ɔwɔ ne nnawɔtwe a ɛdi kan som mu nso ani bɛgye ho.
5.12
Anka atumi aboa me wɔ m’asɔfodie adwuma a manya nyinaa mu–--mpo deɛ manya no ɛnnɛ berɛ yi mu.
8.24
“Na deɛ ɔyɛ nokwafoɔ na ɔnya saa asɔfodie yi mmienu no a maka ho asɛm no,
4.74
Na yɛn nko ara ne abusua a ɛwɔ nkorabata no mu.
2.98
Na ɔnyaaɛ.
3.799
Menyaa saa mpaebɔ no ho mmuaeɛ.
1.66
Agya panyin no akɔmkyene ne mpaeɛ no so ba mfasoɔ nam Awurade so.
5.72
Awurade hyɛ yɛn yei ho bɔ:
3.78
ɔyɔnkoɔ no,
0.4
Wo nim asodie no sɛ ɛwɔ sɛ wode wo frɛ no yɛ adwuma sɛ wobɛsom.
6.4
Mehyira wo seesei sɛ wobɛte Ne dɔ ne N’awerɛhyɛmu nka wɔ Awurade Yesu Kristo din mu,
7.32
Wɔ berɛ kumaa bi a me ne mo wɔ anadwo yi no,
3.76
Honhom no ka wɔn akoma ma wɔgye to mu na wɔnya awerɛkyekyerɛ kyɛn sɛ wɔbɛdi awerɛhoɔ.
8.92
Me wɔ obuo ne anisɔ ma mo pa ara.
2.52
Menyaae a anka obi kakyerɛɛ me deɛ merebɛka no seesei yi.
3.7
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This dataset is made available because of Ghana NLP's volunteer driven research work. Please consider contributing to any of our projects on Github

Twi Speech-Text Parallel Dataset

Dataset Description

This dataset contains 21138 parallel speech-text pairs for Twi (Akan), a language spoken primarily in Ghana. The dataset consists of audio recordings paired with their corresponding text transcriptions, making it suitable for automatic speech recognition (ASR) and text-to-speech (TTS) tasks.

Dataset Summary

  • Language: Twi (Akan) - tw
  • Task: Speech Recognition, Text-to-Speech
  • Size: 21138 audio files > 1KB (small/corrupted files filtered out)
  • Format: WAV audio files with corresponding text files
  • Modalities: Audio + Text

Supported Tasks

  • Automatic Speech Recognition (ASR): Train models to convert Twi speech to text
  • Text-to-Speech (TTS): Use parallel data for TTS model development
  • Keyword Spotting: Identify specific Twi words in audio
  • Phonetic Analysis: Study Twi pronunciation patterns

Dataset Structure

Data Fields

  • audio: Audio file in WAV format
  • text: Corresponding text transcription from paired text file

Data Splits

The dataset contains a single training split with 21138 filtered audio-text pairs.

Dataset Creation

Source Data

The audio data has been sourced ethically from consenting contributors. To protect the privacy of the original authors and speakers, specific source information cannot be shared publicly.

Data Processing

  1. Audio files and corresponding text files were collected from organized folder structure
  2. Text content was read from separate .txt files with matching filenames
  3. Files smaller than 1KB were filtered out to ensure audio quality
  4. Empty text files were excluded from the dataset
  5. Audio was processed using the MMS-300M-1130 Forced Aligner tool for alignment and quality assurance

Annotations

Text annotations are stored in separate text files with matching filenames to the audio files, representing the spoken content in each audio recording.

Considerations for Using the Data

Social Impact of Dataset

This dataset contributes to the preservation and digital representation of Twi, supporting:

  • Language technology development for underrepresented languages
  • Educational resources for Twi language learning
  • Cultural preservation through digital archives

Discussion of Biases

  • The dataset may reflect the pronunciation patterns and dialects of specific regions or speakers
  • Audio quality and recording conditions may vary across samples
  • The vocabulary is limited to the words present in the collected samples

Other Known Limitations

  • Limited vocabulary scope (word-level rather than sentence-level)
  • Potential audio quality variations
  • Regional dialect representation may be uneven

Additional Information

Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Citation Information

If you use this dataset in your research, please cite:

@dataset{twi_words_parallel_2025,
  title={Twi Words Speech-Text Parallel Dataset},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/michsethowusu/twi-words-speech-text-parallel}}
}

Acknowledgments

  • Audio processing and alignment performed using MMS-300M-1130 Forced Aligner
  • Thanks to all contributors who provided audio samples while maintaining privacy protection

Contact

For questions or concerns about this dataset, please open an issue in the dataset repository.
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