Amazon Sage Maker vs Audioshake
Side-by-side comparison · Updated September 2026
| Description | Amazon SageMaker is a comprehensive machine learning service provided by AWS to build, train, and deploy ML models at scale. SageMaker offers tools to streamline the entire machine learning workflow including data preparation, model training and tuning, and deployment across various platforms. It supports popular machine learning frameworks and integrates seamlessly with other AWS services for robust data management and analytics. With features like SageMaker Studio, Data Wrangler, and AutoPilot, users can enhance their productivity and model efficiency throughout the machine learning lifecycle. | AudioShake separates an existing recording into sources such as vocals, instruments, dialogue, music and effects. It also offers speech cleanup, speaker separation, lyric transcription and word-level lyric alignment. Use those outputs in editing, dubbing, remixing or audio analysis, and listen for leakage and changed sounds before delivery. Its lyric transcription is not a general-purpose speech-to-text service; separated speech can instead feed a dedicated transcription workflow. The developer API includes 10 credits on signup. Usage is billed per source-audio minute for each target model, rounding the duration up to the next minute. A 2 minute 10 second recording processed by vocals and instrumental models at one credit per minute each costs six credits. Instrument stems and lyric transcription/alignment cost one credit per minute; dialogue, effects and speech denoise cost 1.5, dereverb two, multi-voice and music removal ten, and music detection 0.5. Credit rates are not dollar prices. Dereverb also reduces noise, so avoid automatically paying for both cleanup models when one meets the task. Choose AudioShake Live for its professional web workflow, Indie for its artist-oriented route, the API for asynchronous jobs and batches, or a separately licensed Local Inference SDK for on-device or self-hosted integration. Check the target model's input limits: multi-voice accepts at most 1.5 hours, while lyric transcription and alignment accept at most 45 minutes. Pilot the required source material and integration before committing to a production pipeline. AudioShake's August 2026 terms identify Audioshake, Inc. Customers retain content ownership and must have the rights to upload and process it. The agreement permits service improvement and development uses of content, while promising not to sell it or use it to train models designed to generate new original musical compositions or sound recordings. That is a narrower promise than a ban on all model training. Confirm the applicable Order Form for third-party or service-bureau integrations and agree retention requirements for confidential audio. |
| Category | Machine Learning | Audio Editing |
| Rating | No reviews | No reviews |
| Pricing | Pricing unavailable | Usage-Based |
| Starting Price | N/A | N/A |
| Use Cases |
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| Tags | machine learningAWSdata preparationmodel trainingmodel deployment | audio source separationmusic stem separationdialogue separationlyric alignmentaudio API |
| Features | ||
| SageMaker Studio | ||
| Data Wrangler | ||
| AutoPilot | ||
| Support for TensorFlow, PyTorch, and MXNet | ||
| Integration with other AWS services | ||
| Streamlined ML workflow | ||
| Scalable model deployment | ||
| Built-in data management tools | ||
| Comprehensive ML lifecycle management | ||
| Enhanced productivity tools | ||
| Music and instrument stem separation | ||
| Dialogue, music and effects separation | ||
| Speech denoise and combined dereverb/denoise | ||
| Multi-speaker separation | ||
| Lyric transcription and word-level alignment | ||
| Asynchronous API jobs, webhooks and batches | ||
| Separate Live, Indie and Local Inference SDK access | ||
| View Amazon Sage Maker | View Audioshake | |
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