Loma Speech to Text: Preserving a Mande Language with AI

Loma (autonym Löömàgòòi) is a Mande language spoken primarily in Lofa County, Liberia, and the Forest Region of Guinea. With roughly 300,000 speakers, it belongs to the Southwestern Mande branch and is closely related to Kpelle and Mende. Loma has a rich oral literature, but its written form — using a Latin-based orthography developed by missionaries in the 20th century — remains underutilized due to limited educational materials. Accurate speech-to-text technology can bridge this gap.

Why Transcribe Loma Audio?

Transcribing Loma audio is not just about converting speech into text. It enables:

• Language documentation: Recording elders and preserving proverbs before they fade.
• Accessibility: Adding subtitles to videos for deaf Loma speakers.
• Education: Helping children learn to read through familiar spoken content.
• Media production: Subtitling news, sermons, and entertainment in Loma.
• Research: Generating written transcripts of interviews in health, agriculture, and development.

Without a reliable ASR tool, all of these tasks require expensive human transcriptionists, who are rare for Loma.

Unique Challenges of Loma Transcription

Loma presents several acoustic and linguistic challenges for automatic speech recognition.

Tonal System

Loma has three level tones — high, mid, low — and contour tones like rising and falling. A single syllable can change meaning entirely with a different pitch. For example:

• lé (high) = to eat
• lè (low) = to kill
• lē (mid) = to go

Speechyou’s tone-aware model captures these distinctions by analyzing pitch contours in 10ms frames, outputting tone markers directly in the transcript.

Vowel Length and Nasalization

Short vs. long vowels and oral vs. nasal vowels are phonemic. ɓā (long a) means ‘to give’, while ɓa (short a) means ‘to come’. Nasalized vowels are represented with a tilde (e.g., ã). Our model is trained on minimal pairs to avoid confusion.

Dialect Variation

Three major dialects are widely recognized: Gizima, Wubome, and Ziema. Differences include:

• Pronunciation of implosive /ɓ/ (stronger in Gizima, weaker in Wubome)
• Vowel harmony patterns
• Lexical borrowings from English (Liberia) vs. French (Guinea)

Speechyou auto-detects the dialect from the first few seconds of audio and applies a specialized acoustic model.

How Speechyou Works for Loma

Using Speechyou is straightforward:

1. Upload an audio or video file (MP3, WAV, MP4, AVI, etc.).
2. Select “Loma” as the source language. Optionally, specify the dialect (Gizima, Wubome, Ziema).
3. Click Transcribe. The AI generates a time-stamped transcript with tone markers.
4. Download as plain text, SRT, or VTT subtitles.

All processing is done in the cloud, and there are no per-minute fees — unlimited transcription is part of the Solo plan.

Use Cases in Detail

Oral History Preservation

Elders in Loma communities hold knowledge about local medicine, genealogies, and traditional law. Recording their speech and converting it to digital text creates a permanent archive. Teachers can then use these texts in schools, reinforcing literacy in both Loma and English.

Community Radio & Videos

Local radio stations like Radio Lofa can add Loma subtitles to broadcasts, helping deaf listeners follow news about elections, farming tips, and health alerts. On Facebook and WhatsApp, subtitled videos spread faster because they are accessible to everyone.

Research & Development

NGOs working in malaria prevention or cocoa farming often interview farmers in Loma. Transcribing these interviews manually costs hundreds of dollars per project. Speechyou’s AI cuts that to zero cost and delivers transcripts in hours.

Literacy and Language Learning

Children who hear Loma at home often struggle to read it because textbooks are rare. With our tool, parents can record themselves telling stories and generate written versions for their children to follow along — a powerful tool for biliteracy.

Competitor Landscape

Most commercial ASR services ignore Loma completely. Google Speech-to-Text, Otter.ai, and Rev do not include it. OpenAI’s Whisper can attempt Loma, but accuracy drops below 60% because it was never trained on Loma data. Speechyou is currently the only AI transcription service with dedicated Loma models covering its major dialects.

Conclusion

Loma speech-to-text is a critical technology for language vitality, education, and media inclusion. Speechyou brings state-of-the-art AI to a language that Big Tech overlooks. Whether you are a linguist documenting an epic, a pastor subtitling a sermon, or a student wanting to read your grandmother’s stories, our tool turns spoken Loma into written Loma — quickly, accurately, and affordably.