Samples

Proof examples for complex Mandarin transcription.

These anonymized examples show how FingerPower handles mixed language, dense terminology, speaker and number sensitivity, and confidential offline scoping.

Samples

Samples organized by transcription risk.

Each example shows the recording challenge, the handling approach, and the difference between rough output and a document that can support research or decisions.

Mandarin-English mixed transcription

Challenge

Bilingual or multilingual speech is difficult because the transcriber must know when a sound is English, an acronym, a brand, or a Chinese homophone. ASR can turn English terms into absurd-looking Chinese.

Handling

A bilingual reviewer checks the context, restores the English terms, and keeps the surrounding Mandarin readable without translating away the original wording.

Raw ASR Draft

他们的扣和瑞腾神到 D30 看是可以的，但是爱了提维偏低，主要是猫的奶贼深没有做起来，特别是因爱普破车子和爱字这两块。

Human-reviewed Output

在 D30 维度，他们的 cohort retention 表现尚可，但 LTV 偏弱。核心原因是 monetization 仍未跑通，尤其是 in-app purchase 与广告变现两条路径。

English terms restored

Bilingual context checked

Analyst-ready phrasing

Terminology-heavy transcription

Challenge

Terminology-heavy recordings in finance, healthcare, manufacturing, semiconductors, and other fields have a higher recognition error rate. The problem is not polishing style; key terms may be heard as unrelated words.

Handling

Review focuses on term correction, acronym normalization, and context checks against the subject matter before the transcript is made readable.

Raw ASR Draft

管理层提到一笔他下降，哥四马军承压，半导体那边的佛托利草菲和 CNP 环节还在爬坡。

Human-reviewed Output

管理层提到 EBITDA 下降，gross margin 承压。半导体业务中，photolithography 与 CMP 环节仍处于爬坡阶段。

Term errors corrected

Acronyms normalized

Subject context checked

Speaker-labeled and number-critical transcription

Challenge

Some transcripts must identify who said what, and numbers cannot be wrong. ASR may merge speakers or mishear figures, such as turning 13.2 billion yuan into 3.2 billion yuan.

Handling

Human review separates the speakers, restores the Q&A structure, and checks revenue figures, percentages, units, and time periods before delivery.

Raw ASR Draft

Speaker 1: Q2 收入是 3.2 亿元，同比增长 8.6%。Speaker 2: 毛利率为什么下降？Speaker 1 李四主要是原材料和汇率影响。

Human-reviewed Output

张三：Q2 收入为 13.2 亿元，同比增长 8.6%。李四：毛利率为什么下降？张三：主要因为原材料和汇率影响。

Named speakers separated

Numbers checked

Q&A structure restored

Confidential offline manual transcription

Challenge

Some recordings should not be uploaded to generic cloud ASR or AI tools because they include sensitive research, internal decisions, or unreleased business information.

Handling

This is a workflow choice, not a different writing style: the transcript is keyed manually from the audio without cloud ASR or AI correction unless the client explicitly approves tool use.

Cloud-tool workflow

Audio is uploaded to a generic cloud ASR or AI tool, a draft is generated, and a reviewer edits the machine output.

Offline manual workflow

A human transcriber listens locally and types the transcript directly with a keyboard. Access, storage, deletion, and tool-exclusion rules are agreed before file transfer.

No generic cloud ASR

No AI correction by default

Tool use agreed in advance