Stories with Tag sound analysis

• Show HN: Resonate – real-time high temporal resolution spectral analysis

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  Posted: 2025-04-15 15:26:13

  Verbose tl;dr

  Resonate is a real-time spectral analysis tool offering high temporal resolution, allowing users to visualize the frequency content of audio signals with millisecond precision. Built using Web Audio API, WebAssembly, and WebGL, it provides a fast and interactive spectrogram display directly in the browser. The tool allows for adjustable parameters such as FFT size and windowing function, facilitating detailed analysis of sound. Its focus on speed and visual clarity aims to provide a user-friendly experience for exploring the nuances of audio in various applications.

  Alexandre François has introduced Resonate, a novel approach to real-time spectral analysis with an exceptionally high temporal resolution. Traditional spectral analysis methods often struggle to capture rapid changes in frequency content over time, resulting in a trade-off between frequency resolution and temporal resolution. Resonate aims to mitigate this limitation by employing a sophisticated algorithm that allows for the precise tracking of frequency components even as they rapidly evolve.

  This technology is implemented as a standalone application, currently available for macOS and Windows. The user interface features a dynamic spectrogram display, providing a visual representation of the frequency spectrum as it changes over time. The high temporal resolution of Resonate enables the observation of fine-grained details and transient events in audio signals that might be missed by conventional spectral analysis tools. This can be particularly valuable in fields like music analysis, sound design, and scientific research where understanding the temporal evolution of frequency components is crucial.

  The core of Resonate's functionality revolves around an innovative signal processing technique. While the specifics of the algorithm are not fully detailed, it is implied that it goes beyond traditional Fourier Transform based methods, allowing for a more nuanced and temporally precise analysis of the frequency content. This results in a spectrogram display that is both highly detailed and responsive to changes in the input signal. The application is designed for real-time operation, meaning that the spectral analysis is performed and displayed with minimal latency, allowing for immediate feedback and interaction with the audio.

  Resonate is presented as a valuable tool for anyone working with audio and requiring detailed spectral information. Its high temporal resolution and real-time capabilities make it particularly well-suited for applications where the rapid changes in frequency content need to be accurately captured and visualized. This could range from analyzing the subtle nuances of a musical performance to studying the complex acoustic signatures of natural phenomena. While currently available as a standalone application, the underlying technology has the potential to be integrated into other audio processing tools and workflows.

  • Spectral Analysis
  • Real-time
  • high temporal resolution
  • audio analysis
  • sound analysis
  • DSP
  • Digital Signal Processing
  • FFT
  • Fast Fourier Transform
  • spectrogram
  • audio visualization
  • Music
  • Sound Design
  • Web Audio API
  • javascript
  • HTML5
  • web application
  • Demo
  • Open Source

  Summary of Comments ( 1 )
  https://news.ycombinator.com/item?id=43694157

  Verbose tl;dr

  HN users generally praised the Resonate project for its impressive real-time spectral analysis capabilities and clean UI. Several commenters with audio engineering or music backgrounds appreciated the high temporal resolution and accuracy, comparing it favorably to existing tools like Spectro, and suggested potential uses in music production, instrument tuning, and sound design. Some questioned the choice of Rust/WebAssembly for performance reasons, suggesting a native implementation might be faster, while others defended the approach due to its cross-platform compatibility. A few users requested features like logarithmic frequency scaling and adjustable FFT parameters. The developer responded to many comments, explaining design choices and acknowledging limitations.

  The Hacker News post "Show HN: Resonate – real-time high temporal resolution spectral analysis" sparked a moderate discussion with several interesting comments.

  One commenter pointed out the inherent trade-off between time and frequency resolution in spectral analysis, referencing the Gabor limit. They expressed interest in seeing how Resonate handles this trade-off and manages the computational complexity, especially in real-time. They also questioned the practical applications of such high temporal resolution, wondering if it truly offers benefits beyond existing methods in fields like music information retrieval (MIR).

  Another user highlighted the challenge of achieving both high temporal and frequency resolution simultaneously. They specifically mentioned the constant-Q transform as an alternative approach that provides good time resolution at higher frequencies and good frequency resolution at lower frequencies, contrasting it with the short-time Fourier transform (STFT) used in Resonate. This commenter also wondered if the project utilized the GPU for accelerated processing, given the computational demands of real-time analysis.

  A third comment explored the possibility of using Resonate for sound design purposes, envisioning the potential for manipulating audio based on its high-resolution spectral representation. They also inquired about the availability of a demo to experiment with the software.

  Further comments included technical questions about the implementation details of Resonate, such as its handling of windowing functions and hop size. One user even proposed the potential use of Resonate in analyzing biological signals like EEGs and ECGs, broadening the scope of applications beyond audio.

  Overall, the discussion revolved around the practicality and potential applications of Resonate's high temporal resolution spectral analysis. Commenters were curious about its performance characteristics, its advantages over existing methods, and its potential uses in various fields. There was a general interest in understanding the technical details and experiencing the software firsthand through a demo.

• Microphone Input Noise Comparison – Avisoft Bioacoustics

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  Posted: 2025-04-06 16:23:53

  Verbose tl;dr

  Avisoft Bioacoustics conducted a microphone comparison test focusing on self-noise levels in quiet recordings. Using a soundproofed chamber, they measured the residual noise floor of various popular field recording microphones and recorders, including models from Sennheiser, Sound Devices, Zoom, and others. The results, presented as audio samples and spectrograms, reveal significant differences in noise performance between devices, highlighting the importance of microphone selection for capturing quiet sounds in nature recording and acoustic monitoring applications. The test demonstrates that some seemingly similar microphones exhibit drastically different noise characteristics, emphasizing the value of empirical testing.

  Avisoft Bioacoustics conducted a comprehensive comparison of microphone input noise levels across a range of audio recording hardware, primarily focusing on devices suitable for bioacoustic research. Their meticulous testing procedure aimed to provide researchers with objective data to inform equipment choices for capturing subtle sounds in nature. The test involved recording silence in a quiet room using various combinations of recorders and microphones, then analyzing the resulting audio files to determine the inherent noise floor of each setup.

  The core of the experiment revolved around measuring the equivalent input noise (EIN) – a standardized metric representing the noise generated by the recording system itself, independent of the connected microphone. This was achieved by calculating the signal-to-noise ratio (SNR) using a calibrated sound source and subsequently utilizing this SNR value, alongside the sensitivity of the microphone, to derive the EIN. This approach allowed for a direct comparison of the noise performance of different recorder preamps. They meticulously documented the precise methodology, including the specific calibration equipment and software employed, fostering transparency and reproducibility.

  The results were presented in a detailed table showcasing the EIN values for a multitude of recorder and microphone combinations, categorized by recorder brand and model. This extensive dataset enabled researchers to readily assess the relative noise performance of different setups and identify the most suitable option for their specific requirements. The data reveals a considerable range in EIN values across the tested equipment, highlighting the significant impact of recorder choice on the overall noise floor. Furthermore, Avisoft Bioacoustics offered insightful observations and commentary on the performance of certain devices, discussing factors contributing to noise levels and potential implications for bioacoustic research. Their analysis underscores the importance of carefully considering recorder noise performance, particularly when dealing with faint sounds of interest in natural environments. The study provides a valuable resource for researchers striving to optimize their recording setup for maximal sensitivity and minimize the interference of unwanted noise in their data.

  • microphone
  • audio recording
  • noise comparison
  • Avisoft Bioacoustics
  • sound analysis
  • field recording
  • wildlife recording
  • ultrasonic recording
  • recorder tests
  • audio equipment
  • Sound Quality
  • noise floor
  • signal-to-noise ratio

  Summary of Comments ( 2 )
  https://news.ycombinator.com/item?id=43602652

  Verbose tl;dr

  HN users discussed the methodology of the Avisoft microphone comparison, pointing out that the self-noise measurements weren't standardized (using different gain settings and potentially different preamps) which makes comparisons difficult. Several commenters wished for more expensive microphones to be included in the test, like the Sennheiser MKH series and Sound Devices recorders. Some questioned the value of the SNR measurements given the uncontrolled variables. Finally, a few users offered alternative methods for comparing microphone noise, such as using a quiet, controlled environment and normalizing the recordings. Overall, the consensus was that while the data is interesting, it's not scientifically rigorous enough for definitive conclusions about microphone performance.

  The Hacker News post titled "Microphone Input Noise Comparison – Avisoft Bioacoustics" has generated several comments discussing the linked article's methodology and findings regarding microphone noise levels.

  Several commenters focus on the importance of considering the entire recording chain when evaluating noise. One user points out that the noise floor measurements might be dominated by the preamplifier's noise rather than the microphone itself, especially with low-output microphones. They suggest that using higher-gain, lower-noise preamps could significantly alter the results. Expanding on this, another commenter emphasizes that the cable used between the microphone and preamp can also be a significant source of noise, particularly in longer cable runs. They advocate for testing with short, high-quality cables to minimize this factor.

  Another key point raised is the specific application of these microphones. While the tests focus on low-level sounds, one commenter notes that for louder sounds, the self-noise of the microphone becomes less critical compared to its maximum sound pressure level (SPL) handling capability. This highlights the importance of choosing a microphone based on the intended recording environment and expected sound intensity. Another user echoes this sentiment, suggesting that for many nature recording applications, the low-frequency rumbling from wind or handling noise is a bigger concern than the minute self-noise levels measured in the tests.

  The methodology of the testing also draws some scrutiny. One commenter questions the use of A-weighting in the measurements, arguing that it is designed for human hearing and may not be appropriate for evaluating the full spectrum of noise relevant to bioacoustic recordings, where ultrasonic frequencies can be important. They suggest that a flat frequency response or a different weighting curve might be more suitable.

  Finally, some comments delve into specific technical details, like the importance of impedance matching between the microphone and preamp, the role of phantom power, and the challenges of measuring extremely low noise levels accurately. One user mentions the possibility of thermal noise within the microphone itself being a limiting factor.

  Overall, the comments offer valuable perspectives on interpreting the microphone noise comparison, emphasizing the importance of considering the entire recording system, the intended application, and the nuances of the measurement techniques. They provide context beyond the raw data presented in the article and highlight the complexities of achieving truly low-noise recordings.