Types of Microphones and How to Choose Them<\/h2>\n\n\n\nMicrophone Types and Mechanisms<\/h3>\n\n\n\n
Microphones convert sound into electrical signals using various methods. The two most representative types are Condenser<\/strong> and Dynamic<\/strong> microphones. Their differences are as follows:<\/p>\n\n\n\n Condenser Microphones<\/strong><\/p>\n\n\n\n Dynamic Microphones<\/strong><\/p>\n\n\n\n In field recording, where delicate sounds are often the focus, condenser microphones are primarily used. Additionally, there are specialized microphones such as Hydrophones<\/strong> (for underwater) and Contact Microphones<\/strong> (for vibration in solids) alongside standard air-pressure microphones.<\/p>\n\n\n\n Microphones have different directional characteristics. Common patterns include Omnidirectional, Cardioid, Supercardioid, and Bidirectional. These are chosen based on the target source and environment.<\/p>\n\n\n\n Omnidirectional<\/strong><\/p>\n\n\n\n Cardioid<\/strong><\/p>\n\n\n\n Supercardioid<\/strong><\/p>\n\n\n\n Bidirectional<\/strong><\/p>\n\n\n\n Experiment<\/strong> <\/p>\n\n\n\n Recorded sound is an analog signal converted into digital data through sampling<\/strong>. Two key metrics define this process: Sampling Rate and Bit Depth.<\/p>\n\n\n\n The sampling rate is the “number of times a signal is measured per second,” expressed in Hertz (Hz). Standard CD quality is 44.1 kHz, meaning it measures 44,100 times per second.<\/p>\n\n\n\n According to the Nyquist Theorem (Sampling Theorem)<\/strong>, to accurately convert an analog signal into digital, the sampling rate must be at least twice the highest frequency present in the signal.<\/p>\n\n\n\n In field recording, you set the sampling rate on your device. While the choice depends on the intended use, recording at “Hi-Res” rates like 96 kHz or 192 kHz provides greater flexibility for post-processing, though it results in larger file sizes.<\/p>\n\n\n\n Bit depth represents the amount of information per sample. Higher bit depth allows for capturing finer nuances and recording with high fidelity while minimizing distortion noise. Note that bit depth does not relate to frequency resolution.<\/p>\n\n\n\n The analog counterpart to bit depth is Dynamic Range<\/strong>\u2014the ratio between the maximum and minimum signal values a system can handle. Higher bit depth increases the resolution of the amplitude, widening the dynamic range:<\/p>\n\n\n\n Higher bit depth increases the potential to express a wider dynamic range. However, other factors like the noise floor and saturation levels also affect the final dynamic range. Bit depth can be thought of as the “fineness of the container” for expressing dynamic range.<\/p>\n\n\n\n Common field recording standards are 24-bit or 32-bit float. 32-bit float, now common in modern devices, performs extremely fine division, including decimals. This is covered in another article: “Introduction to Field Recording | 32-bit float Recording.”<\/strong><\/p>\n\n\n\n In summary, higher sampling rates enable more accurate recording of frequency components, while higher bit depths allow for more nuanced representation of sound pressure variations.<\/p>\n\n\n\n <\/p>\n\n\n\n Stereo recording typically involves spacing two microphones a few meters away from the target, depending on the recording content.<\/p>\n\n\n\n Experiment<\/strong> <\/p>\n<\/blockquote>\n\n\n\n In field recording, adjusting the input recording level is crucial. Proper level settings significantly affect sound quality. Levels that are too low increase noise, while levels that are too high cause clipping.<\/p>\n\n\n\n Adjust levels so peaks fall between -6 and -12 dBFS<\/strong>. In field recording, aiming for -12 dBFS provides a margin for sudden loud sounds.<\/p>\n\n\n\n Noise is inevitable in the field. Wind is the primary enemy; use windjammers<\/strong>, shock mounts<\/strong>, and protectors to mitigate physical vibrations and wind interference. Be aware of electromagnetic interference (EMI) in electronic environments. While complete elimination is impossible, monitoring with headphones and “enjoying the noise itself” can be part of the process.<\/p>\n\n\n\n <\/p>\n\n\n\n This is the theoretical foundation for converting analog waves (continuous) into digital data (discrete). To digitize, values are taken as “samples” at fixed intervals.<\/p>\n\n\n\n Aliasing is a “frequency misidentification (folding error)” that occurs when the sampling rate is insufficient. If the rate is below the Nyquist frequency, high-frequency sounds are incorrectly recorded as low-frequency components, causing noise or distortion. Recorders typically have an Anti-aliasing filter<\/strong> to remove these components before sampling.<\/p>\n\n\n\n <\/p>\n\n\n\n Digital filters and EQ (Equalizers) are tools used to process and optimize recorded sound. They are used to control the frequency components of sound, emphasizing or removing them depending on the purpose.<\/p>\n\n\n\n A digital filter is a process that uses Digital Signal Processing (DSP) to pass or block specific frequency bands. The main types of filters are as follows:<\/p>\n\n\n\n FIR (Finite Impulse Response) filters and IIR (Infinite Impulse Response) filters are the two basic forms of digital filters. Each has its own characteristics, advantages, and disadvantages, and they are used differently depending on the application.<\/p>\n\n\n\n An EQ (Equalizer) is a tool that allows you to freely boost (amplify) or cut (attenuate) frequency bands of sound, and it is a type of digital filter. The main types of EQ are as follows:<\/p>\n\n\n\n In field recording, there are various types of noise depending on the situation and the recording subject, so settings are made with their use in mind.<\/p>\n\n\n\n Experiment<\/strong> <\/p>\n\n\n\n <\/p>\n\n\n\n By understanding recording equipment and digital signal processing, your decisions\u2014\u201cWhy this setting?\u201d<\/em> or \u201cWhy this mic?\u201d<\/em>\u2014move from guesswork to clear, evidence-based choices.<\/p>\n\n\n\n <\/p>\n\n\n\n This book introduces the idea of the \u201csoundscape\u201d\u2014a term the author created\u2014to describe the sounds that surround us in everyday life. From the natural sounds of the past to the noise of modern cities and machines, our acoustic environment has become increasingly complex.<\/p>\n\n\n\n The author argues that as noise levels rise, our ability to truly listen and notice subtle sounds has declined. He encourages us to become more aware of the sounds around us, to listen more closely, and to recognize the difference between enriching sounds and harmful noise.<\/p>\n\n\n\n Just as we\u2019re concerned about air and water pollution, we should also care about sound pollution. The book offers ways to classify sounds, judge their quality, and includes simple exercises and \u201csoundwalks\u201d to help us tune in. It\u2019s a thoughtful guide to understanding our sonic world\u2014past, present, and future.<\/p>\n\n\n\n\n
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Microphone Polar Patterns<\/h3>\n\n\n\n
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Record the same environment with multiple microphones and compare their frequency characteristics and noise resistance. Pay attention to the differences in three-dimensionality and “airiness.”<\/p>\n<\/blockquote>\n\n\n\nUnderstanding Sampling Rate and Bit Depth<\/h2>\n\n\n\n
Sampling Rate<\/h3>\n\n\n\n
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Bit Depth<\/h3>\n\n\n\n
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Understanding Ambient Sound and Microphone Placement (Common Miking Techniques)<\/h3>\n\n\n\n
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The most basic method. Two omnidirectional microphones are placed parallel to each other, creating time differences in sound arrival to produce a stereo effect. This setup captures a wide sound field with minimal interference.<\/li>\n\n\n\n
Uses two unidirectional microphones placed at a 90-degree angle, overlapping at the same point. This enhances positional accuracy and captures sound naturally without an overly wide sound field.<\/li>\n\n\n\n
Both use two unidirectional microphones. ORTF places them 17 cm apart at a 110-degree angle, while NOS places them 30 cm apart at a 90-degree angle. These setups excel at realistically reproducing the sound field, balancing volume and stereo imaging. ORTF was developed by the French Broadcasting Corporation, and NOS by the Dutch Broadcasting Corporation.<\/li>\n<\/ul>\n\n\n\n\n
Record the same sound at “44.1kHz \/ 16-bit” and “96kHz \/ 24-bit” to compare. Experience the expanded sound field and subtle differences with higher sampling rates.<\/p>\n\n\n\nGain Structure and Noise Management<\/h2>\n\n\n\n
Ideal Level Design<\/h3>\n\n\n\n
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Managing Noise<\/h3>\n\n\n\n
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Sampling Theory and Aliasing<\/h2>\n\n\n\n
Sampling Theory<\/h3>\n\n\n\n
Aliasing<\/h3>\n\n\n\n
Rate Selection<\/td> 44.1 kHz+ recommended. 96 kHz+ is effective for bird songs\/insects.<\/td><\/tr> Hi-Res Recording<\/td> 192 kHz captures ultrasonic spatial info.<\/td><\/tr> Equipment<\/td> Ensure recorders\/mics have proper frequency response\/filters.<\/td><\/tr> Downsampling<\/td> Use proper resampling (interpolation\/filters) when lowering rates.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n How Digital Filters and EQ Work<\/h2>\n\n\n\n
Digital Filter<\/h3>\n\n\n\n
Filter Type<\/th> Function<\/th> Example Use<\/th><\/tr><\/thead> Low-Pass Filter (LPF)<\/td> Attenuates frequencies higher than the specified cutoff frequency.<\/td> Removal of high-frequency noise, mitigation of wind hiss.<\/td><\/tr> High-Pass Filter (HPF)<\/td> Attenuates frequencies lower than the specified cutoff frequency.<\/td> Removal of microphone proximity effect and low-frequency noise (traffic, wind).<\/td><\/tr> Band-Pass Filter (BPF)<\/td> Passes only a specific frequency band.<\/td> Emphasizing only the target sound, such as bird songs.<\/td><\/tr> Band-Stop (Notch) Filter<\/td> Removes a specific frequency band.<\/td> Removal of hum noise (50Hz\/60Hz), etc.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n FIR and IIR Filters<\/h3>\n\n\n\n
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Item<\/th> FIR Filter<\/th> IIR Filter<\/th><\/tr><\/thead> Stability<\/td> Always stable<\/td> Potential to become unstable<\/td><\/tr> Phase Characteristics<\/td> Linear phase is possible (no waveform distortion)<\/td> May involve phase distortion<\/td><\/tr> Feedback<\/td> None (Output depends only on input)<\/td> Yes (Output includes past outputs)<\/td><\/tr> Computational Load<\/td> High (High cost)<\/td> Low (Efficient)<\/td><\/tr> Ease of Implementation<\/td> Easy<\/td> Requires caution for stabilization and design<\/td><\/tr> Use Cases<\/td> Audio\/image processing where high quality is required<\/td> Real-time processing, control systems, etc.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n Purpose<\/th> Recommended Filter<\/th> Reason<\/th><\/tr><\/thead> Sound shaping or clean editing after recording<\/td> FIR<\/td> Advantageous when you want to remove specific frequencies without changing the waveform (e.g., cleanly extracting bird voices).<\/td><\/tr> Real-time processing (Live noise removal, monitoring during recording)<\/td> IIR<\/td> Suitable for applications requiring immediate response with light processing.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n EQ (Equalizer)<\/h3>\n\n\n\n
Type<\/th> Characteristics<\/th> Use Case<\/th><\/tr><\/thead> Parametric EQ<\/td> Frequency, bandwidth, and gain can be set freely.<\/td> Precise sound creation and removal of unwanted sounds.<\/td><\/tr> Graphic EQ<\/td> Adjusts pre-determined frequency bands with fixed sliders.<\/td> Convenient for live sound and simple adjustments.<\/td><\/tr> Shelving EQ (Low\/High Shelf)<\/td> Boosts\/cuts everything below (or above) a specified frequency at once.<\/td> Adjusting “airiness” (highs) or deep bass (lows).<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n Situation<\/th> EQ\/Filter to Use<\/th> Reason<\/th><\/tr><\/thead> Source containing wind noise<\/td> High-Pass Filter<\/td> Cut low-frequency wind noise (e.g., below 80\u2013150Hz).<\/td><\/tr> Wanting to extract only bird songs<\/td> Band-Pass or Parametric EQ<\/td> Emphasize bird voices while suppressing surrounding noise.<\/td><\/tr> Deep bass from distant cars resonating<\/td> Low-Pass or EQ<\/td> Clear the sound field by cutting low frequencies.<\/td><\/tr> Electromagnetic noise present<\/td> Notch Filter<\/td> Remove specific frequencies such as 50Hz\/60Hz hum noise.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Implement these using audio editing software or programming tools such as Processing or openFrameworks. Use filters to extract only specific bands and visually observe the structure of the sound.<\/p>\n\n\n\nExperiment<\/h2>\n\n\n\n
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“Judgment” is a Hybrid of Knowledge and Experience<\/h2>\n\n\n\n
Recommended Book <\/em><\/h2>\n\n\n\n
The Soundscape<\/a> – R. Murray Schafer <\/h3>\n\n\n\n
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