Automatic Music Transcription

We develop your AI solution. With expertise in advanced spectral analysis, audio processing algorithms, and modern AI techniques, our team tailors custom designs blending traditional signal processing with AI.

Recent advancements in deep learning research have significantly enhanced the capability to detect note events in recorded audio and perform polyphonic pitch detection.

Renowned global players like Spotify and Google have contributed to the striking performance of current AMT systems, which made it possible to accurately identify the beginnings (onsets) and endings (offsets) of notes across recordings featuring a variety of instruments.

The choice of model architecture can severely depend on the application needs and the characteristics of the used instrument, requiring expertise both when training custom models, but also when evaluating the suitability of available open models from literature. The demands of postprocessing are similarly multifaceted, e.g., necessitating different approaches when requiring real-time processing, or when matching to predetermined expected notes.

PhonicScore has established itself as a leading expert in the field of note detection system development, thanks to our successful deployment of note detection systems in both our own products and those of our partners. This experience positions us uniquely as a global leader in the AMT domain.

Our Toolset

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Let’s Create Together

Connect with us to explore how we can make your vision a reality. Join us in shaping the future.

How do we build your product?

We can support in every phase of product development. To enhance productivity and accelerate time to market, we typically employ a proven, systematic approach to collaboratively build the product with you.

01

Concept and Ideation

Define the core idea, identify the problem we are solving, the target audience, and the essential differentiating features.

02

Feasibility Study

Assess the technical feasibility and market viability of the product through preliminary research and analysis.

03

Planning and Design

Outline the scope of a Minimum Viable Product (MVP) focusing on essential features only, and plan the project timeline, budget, and resources. Design initial wireframes or mockups.

04

Development of an MVP

Develop the MVP using rapid development cycles with continuous integration and testing, focusing on creating a functional prototype.

05

Testing and Iteration

Test the MVP internally and with users to gather feedback, and iteratively refine the product based on this feedback.

06

Launch

Officially launch the MVP to a broader audience, including marketing and user support preparations.

07

Evaluation and Scaling

Analyze the performance of the MVP against objectives, and scale the product by adding features and expanding the market reach if the MVP is successful.

Why Choose Us

Discover the reasons that set us apart.

Proficiency

With extensive expertise in audio processing, machine learning, and software development, we are the ideal partner for implementing audio and AI projects.

Approach

We use modern development tools and project management procedures to maximize productivity while retaining the highest quality outcomes for your product.

Team

We are tech enthusiasts, innovators and we live music. We’re driven to revolutionize your product by harnessing the latest in AI advancements.

12+

Years of Deep Tech experience

100%

Client satisfaction

1400+

GitHub Stars

3 Countries

Our team is based in Austria, India and the USA

Why use AI?

Enhanced Audio Quality

AI algorithms can automatically improve audio clarity, reduce noise, and optimize sound quality. This is particularly useful in environments with variable acoustic conditions, enabling consistent audio quality across different scenarios.

Personalization

AI algorithms can adapt audio content to the preferences of individual users. For instance, streaming services use AI to recommend music based on listening habits. In software interfaces, AI can adjust the audio dynamics to suit user-specific hearing profiles.

Cost Efficiency and Scalability

Automating various audio processing tasks with AI reduces the need for manual intervention, lowering costs and improving efficiency. AI systems can scale more easily than human-based systems, managing large-scale audio processing tasks without a proportional increase in resource investment.

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Our Story

PhonicScore is the CultTech company from Vienna, Austria, the city of music, focusing on Music and Education. Since 2012 we are developing mobile apps, software libraries, plugins and AI solutions.

Let’s Create Together

Connect with us to explore how we can make your vision a reality. Join us in shaping the future.

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