Datasets:
audio
audioduration (s) 1.06
3.21
| hon
stringlengths 8
38
| rom
stringlengths 8
38
|
|---|---|---|
I woke up early this morning.
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I woke up early this morning.
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The sky was clear and blue.
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The sky was clear and blue.
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I made a cup of hot tea.
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I made a cup of hot tea.
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The room felt quiet and calm.
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The room felt quiet and calm.
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I sat by the window for a while.
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I sat by the window for a while.
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A light breeze moved the curtains.
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A light breeze moved the curtains.
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The street outside was still empty.
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The street outside was still empty.
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I checked my phone for new messages.
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I checked my phone for new messages.
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Breakfast was simple but satisfying.
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Breakfast was simple but satisfying.
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I took a short walk after eating.
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I took a short walk after eating.
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The trees looked green and fresh.
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The trees looked green and fresh.
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Birds were singing nearby.
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Birds were singing nearby.
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I heard footsteps on the sidewalk.
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I heard footsteps on the sidewalk.
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A dog barked in the distance.
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A dog barked in the distance.
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The sun slowly climbed higher.
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The sun slowly climbed higher.
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Clouds drifted across the sky.
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Clouds drifted across the sky.
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The weather felt comfortable today.
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The weather felt comfortable today.
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I enjoyed the peaceful moment.
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I enjoyed the peaceful moment.
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Time seemed to pass slowly.
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Time seemed to pass slowly.
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I returned home feeling relaxed.
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I returned home feeling relaxed.
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I opened a book on my desk.
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I opened a book on my desk.
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The pages smelled slightly old.
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The pages smelled slightly old.
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I read a few chapters quietly.
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I read a few chapters quietly.
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The story was easy to follow.
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The story was easy to follow.
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Some sentences made me smile.
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Some sentences made me smile.
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I paused to think about the ideas.
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I paused to think about the ideas.
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The room grew warmer in the afternoon.
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The room grew warmer in the afternoon.
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I drank some cold water.
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I drank some cold water.
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The light changed as the sun moved.
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The light changed as the sun moved.
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Shadows stretched across the floor.
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Shadows stretched across the floor.
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I closed the book and stood up.
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I closed the book and stood up.
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The chair made a soft sound.
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The chair made a soft sound.
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I looked around the room.
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I looked around the room.
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Everything felt familiar and safe.
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Everything felt familiar and safe.
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I organized my notes on the table.
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I organized my notes on the table.
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The clock ticked steadily.
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The clock ticked steadily.
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The day continued quietly.
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The day continued quietly.
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I felt calm and focused.
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I felt calm and focused.
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Small moments can feel meaningful.
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Small moments can feel meaningful.
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I appreciated the simple routine.
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I appreciated the simple routine.
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Bonjour.
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Bonjour.
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Je m’appelle Zoey.
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Je m’appelle Zoey.
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Je suis étudiante.
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Je suis étudiante.
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J’aime le français.
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J’aime le français.
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Il fait beau aujourd’hui.
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Il fait beau aujourd’hui.
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C’est une phrase simple.
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C’est une phrase simple.
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Je parle lentement.
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Je parle lentement.
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Le microphone est ici.
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Le microphone est ici.
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Cette pièce est calme.
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Cette pièce est calme.
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Merci beaucoup.
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Merci beaucoup.
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Dataset Description
This dataset contains 50 short speech recordings prepared for a text-to-speech (TTS) task. The recordings were produced by a single speaker in a quiet indoor environment using the same recording device throughout. The dataset includes 40 English sentences and 10 simple French sentences.
Issues Encountered and Solutions
The primary issue encountered during data preparation was audio segmentation. Manual segmentation proved excessively time-consuming, so the “timestamp annotation” feature was employed to automate the process. A secondary challenge arose from natural pauses within sentences, which rendered automatic segmentation inaccurate; interference from sounds such as swallowing or exhaling also impacted results. This issue was mitigated by re-recording the audio with deliberate one-to-two-second silences between sentences, thereby enhancing the accuracy of silence detection. Another problem concerned character encoding errors when processing French accented characters in the metadata file. This was resolved by saving the metadata.csv file using UTF-8 encoding and avoiding spreadsheet software that might alter the file's encoding.
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