据 AlphaMoat 统计,截至 2026-09,Audiobook 累计下载 1,173 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 4,948 位,在「设计创意」分类(512 个)中排名第 496 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 24 | 989 | 1 | - |
| SkillHub ↗ | 158 | 1,173 | 1 | — |
各平台的计数口径不同,统计时间不一致。
支持按章节处理长文本、为叙述者和角色配置不同声音,并组合音频及章节元数据。生成过程使用 SenseAudio 外部 TTS API;未经批准不要提交机密或受版权限制的稿件,生成文件应存放在获准目录。 需把 SenseAudio 凭据配置为 API_KEY,并准备 requests、pydub、mutagen 等 Python 依赖。先审核修复样例章节元数据代码,再验证样章后批量生成;样例不等于已实测的端到端流程。不需留存时清理生成产物。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 1,173 | — | 1 |
| 2026-08 | 989 | +12.3% | 1 |
| 2026-07 | 881 | +29.7% | 1 |
| 2026-06 | 679 | +17.7% | 1 |
| 2026-05 | 577 | — | 1 |
| 2026-03 | 341 | — | 1 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
name: senseaudio-audiobook-generator
description: Generate audiobooks from novels and long-form text with chapter management and character voices. Use when users mention audiobooks, narrating books, or converting lengthy written content to audio.
compatibility:
required_credentials:
- name: SENSEAUDIO_API_KEY
description: API key from https://senseaudio.cn/platform/api-key
env_var: API_KEY
homepage: https://senseaudio.cn
source: https://github.com/anthropics/skills---
# SenseAudio Audiobook Generator
Convert novels, books, and long-form written content into professional audiobooks with natural narration and character voices.
## What This Skill Does
This skill helps you create audiobooks by:
- Converting long texts (novels, books, articles) into audio
- Automatically handling chapter divisions
- Supporting multiple character voices for dialogue
- Distinguishing between narration and character speech
- Managing long content with automatic chunking
## When to Use This Skill
Use this skill when you need to:
- Create audiobooks from novels or books
- Convert long-form articles to audio
- Generate narrated versions of written content
- Produce audio for e-learning materials
- Create accessible audio versions of text documents
## How It Works
### Basic Workflow
1. **Prepare the text** - Format with chapter markers and dialogue tags
2. **Configure narration** - Choose narrator voice and character voices
3. **Process chapters** - Generate audio for each chapter or section
4. **Combine audio** - Merge all segments into complete audiobook
5. **Add metadata** - Include chapter markers and timestamps
### Text Format
Structure your content like this:
```
# Chapter 1: The Beginning
[Narrator]
It was a dark and stormy night. The old mansion stood alone on the hill.
[Character: John, Voice: male_0004_a]
"I don't think we should go in there," John whispered nervously.
[Character: Sarah, Voice: female_0006_a]
"Don't be silly. It's just an old house."
[Narrator]
They pushed open the creaky door and stepped inside.
```
### Voice Configuration
**Narrator voice**: Choose a clear, neutral voice for narration
- Recommended: male_0004_a (calm male) or female_0027_a (clear female)
- Speed: 0.9-1.0 for comfortable listening
- Pitch: 0 (neutral)
**Character voices**: Assign distinct voices to each character
- Use different voice IDs for different characters
- Adjust pitch slightly to differentiate (+2/-2)
- Vary speed for character personality (excited: 1.1, calm: 0.9)
### Chapter Management
For long books, process by chapters:
```python
chapters = [
{"title": "Chapter 1", "text": "...", "start_time": 0},
{"title": "Chapter 2", "text": "...", "start_time": 1234},
# ...
]
```
Benefits:
- Easier to manage and debug
- Allows chapter navigation in audio players
- Can resume generation if interrupted
- Enables parallel processing
## Implementation Steps
### Step 1: Parse and Structure Content
Extract structure from the text:
```python
import re
def parse_audiobook_text(text):
sections = []
current_section = {"type": "narrator", "text": "", "voice": "male_0004_a"}
for line in text.split('\n'):
# Chapter markers
if line.startswith('# Chapter'):
if current_section["text"]:
sections.append(current_section)
sections.append({"type": "chapter", "title": line[2:]})
current_section = {"type": "narrator", "text": "", "voice": "male_0004_a"}
# Narrator
elif line.startswith('[Narrator]'):
if current_section["text"]:
sections.append(current_section)
current_section = {"type": "narrator", "text": "", "voice": "male_0004_a"}
# Character dialogue
elif match := re.match(r'\[Character: (\w+), Voice: ([\w_]+)\]', line):
if current_section["text"]:
sections.append(current_section)
current_section = {
"type": "character",
"character": match.group(1),
"voice": match.group(2),
"text": ""
}
else:
current_section["text"] += line + " "
if current_section["text"]:
sections.append(current_section)
return sections
```
### Step 2: Generate Audio Segments
For each section, call the TTS API:
```python
import requests
import binascii
def generate_audio_segment(text, voice_id, output_file, speed=1.0):
url = "https://api.senseaudio.cn/v1/t2a_v2"
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
payload = {
"model": "SenseAudio-TTS-1.0",
"text": text,
"stream": False,
"voice_setting": {
"voice_id": voice_id,
"speed": speed,
"vol": 1.0,
"pitch": 0
},
"audio_setting": {
"format": "mp3",
"sample_rate": 32000,
"bitrate": 128000,
"channel": 2
}
}
response = requests.post(url, headers=headers, json=payload)
data = response.json()
# Decode hex audio
audio_hex = data['data']['audio']
audio_binary = binascii.unhexlify(audio_hex)
# Save to file
with open(output_file, 'wb') as f:
f.write(audio_binary)
return data['extra_info']['audio_length'] # Duration in ms
```
### Step 3: Handle Long Text
Split long chapters into manageable chunks:
```python
def chunk_text(text, max_length=5000):
"""Split text at sentence boundaries"""
sentences = re.split(r'([.!?]+\s+)', text)
chunks = []
current_chunk = ""
for i in range(0, len(sentences), 2):
sentence = sentences[i]
separator = sentences[i+1] if i+1 < len(sentences) else ""
if len(current_chunk) + len(sentence) + len(separator) > max_length:
if current_chunk:
chunks.append(current_chunk.strip())
current_chunk = sentence + separator
else:
current_chunk += sentence + separator
if current_chunk:
chunks.append(current_chunk.strip())
return chunks
```
### Step 4: Combine Audio Files
Merge all segments into a complete audiobook:
```python
from pydub import AudioSegment
def create_audiobook(segments, output_file, chapter_markers=None):
audiobook = AudioSegment.empty()
chapter_times = []
current_time = 0
for i, segment_file in enumerate(segments):
# Load segment
segment = AudioSegment.from_mp3(segment_file)
# Check if this is a chapter start
if chapter_markers and i in chapter_markers:
chapter_times.append({
"chapter": chapter_markers[i],
"time": current_time
})
# Add segment
audiobook += segment
current_time += len(segment)
# Add pause between segments (300ms)
if i < len(segments) - 1:
audiobook += AudioSegment.silent(duration=300)
current_time += 300
# Export with metadata
audiobook.export(
output_file,
format="mp3",
bitrate="128k",
tags={
"title": "Audiobook",
"artist": "SenseAudio TTS",
"album": "Generated Audiobook"
}
)
return chapter_times
```
## Advanced Features
### Dialogue Enhancement
Make dialogue more natural:
- Add slight pauses before character speech: `<break time=200>`
- Vary character emotions based on context
- Use different pitch for different characters
### Narration Styles
Adjust narrator voice for different genres:
- **Fiction**: Slightly expressive (speed: 1.0, varied pitch)
- **Non-fiction**: Clear and steady (speed: 0.95, neutral pitch)
- **Children's books**: Animated (speed: 1.1, varied emotions)
- **Technical**: Slow and clear (speed: 0.9, neutral)
### Chapter Markers
Add ID3 tags for chapter navigation:
```python
from mutagen.mp3 import MP3
from mutagen.id3 import ID3, CHAP, TIT2, CTOCFlags
def add_chapter_markers(mp3_file, chapters):
audio = MP3(mp3_file, ID3=ID3)
# Add chapters
for i, chapter in enumerate(chapters):
audio.tags.add(
CHAP(
element_id=f"chp{i}",
start_time=chapter["time"],
end_time=chapters[i+1]["time"] if i+1 < len(chapters) else len(audio.info.length * 1000),
sub_frames=[TIT2(text=chapter["chapter"])]
)
)
audio.save()
```
### Progress Tracking
For long books, track progress:
```python
def generate_audiobook_with_progress(sections, output_dir):
total = len(sections)
completed = 0
for i, section in enumerate(sections):
output_file = f"{output_dir}/segment_{i:04d}.mp3"
# Skip if already generated
if os.path.exists(output_file):
completed += 1
continue
# Generate audio
generate_audio_segment(
section["text"],
section["voice"],
output_file=output_file
)
completed += 1
print(f"Progress: {completed}/{total} ({completed*100//total}%)")
```
## Error Handling
Common issues:
**Text too long**: Chunk into smaller segments (max 10,000 chars per request)
**Voice consistency**: Save voice mappings to ensure same character uses same voice
**Memory issues**: Process chapters separately, don't load entire book at once
**API rate limits**: Add delays between requests (e.g., 1 second)
## Output Format
The skill produces:
- Individual chapter audio files (MP3)
- Complete audiobook file (MP3)
- Chapter markers and timestamps (JSON)
- Metadata file with voice mappings and settings
## Example Usage
**User request**: "Convert this novel into an audiobook with different voices for each character"
**Skill actions**:
1. Parse the novel text and identify chapters
2. Extract character dialogue and assign voices
3. Generate audio for each section
4. Combine all audio with chapter markers
5. Export final audiobook with metadata
6. Provide playback instructions and chapter list
## Tips for Best Results
- Use consistent voice IDs for the same character throughout
- Add natural pauses between paragraphs and chapters
- Test a sample chapter before processing the entire book
- Keep narrator voice neutral and clear
- Use higher quality settings (44100 Hz) for final production
- Consider adding background ambience for immersive experience
## Reference
For detailed API documentation, see the SenseAudio TTS API reference in the `references/` directory.
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数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。