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WARNING: This document includes toxic language. This is not included to cause offense but to help in showing example language that is detected for each category at each slider level.
Bleep – Powered by Intel® uses AI acceleration to detect and redact incoming audio based on recipient user preferences, offering users the option to better manage their in-game voice chat experience. The project has been developed in partnership between Intel and Spirit AI. The app combines the two company’s AI models with the Windows audio architecture. From the UI, the user can both select which toxicity filters they would like to enable as well as review the conversation transcript and associated analysis.
On / Off Switch : When Bleep is “on” and at least one of the categories is set to anything other than “none”, Bleep will attempt to redact the speech for the enabled categories using the chosen settings for those categories. Note that the application that makes up the UI is not the entirety of Bleep and the functionality that analyzes and modifies the audio data is a separate process. This means that closing the UI has no effect on whether Bleep is running or not. A user must flip the switch to “off” to stop Bleep from delaying and attempting to redact the audio stream.
“Redaction delay” slider : This slider controls the delay introduced to the audio being analyzed. The value can be changed without having to restart any process but changing the value will result in either missed audio if the delay is reduced or a moment of silence if the delay is increased. This is to be expected and an unavoidable result of changing the buffer time.
“How much should we bleep?” slider:
Note that “low” settings will be least sensitive when filtering toxic speech and may miss certain pronunciations, derivatives, etc., while “high” is the most sensitive setting to avoid all ambiguity and context, which can potentially over redact speech. Detailed information is discussed in each category section.
“Which devices should Bleep integrate with?” check boxes : There is a check box for every audio device listed in the windows registry that includes the “FxProperties” properties key and is also set to enabled. The check for the “FxProperties” properties key is how the software knows the audio device can support the APO integration. Note that the check for a device to be enabled has the following implication: Devices that are connected via the audio jack are automatically marked as disabled unless they are plugged in. This has the consequence that a pair of headphones will only show up if it is plugged in. Changing these settings will require a system restart so the change in APO integration can be applied.
“What we are bleeping” : The real-time nature of audio redaction means that there may be insufficient context to know if a word is meant in a toxic way or more of a friendly “banter” kind of way as it is being said. The software doesn’t attempt to make this distinction when performing the redaction task. Please see the section on the transcript in the Review Sessions View section of this document for more information about how linguistic context is utilized. Note that the classification process is inherently multi-class which means that some language will fall into multiple categories. The operation to determine whether redaction should take place is an “OR” operation. If any of the ways a term is classified falls into a category enabled by a user, it will be redacted. If a user wants to hear specific language, they may have to turn off multiple categories to see a change in the behavior of Bleep. The detected categories for a given paragraph in the transcript are displayed in the annotated transcript.
This filter catches language that relates to somebody’s physical appearance or mental capabilities. At the low slider setting only the most offensive ableist language will be caught, for example derogatory references to specific disabilities and neurodivergent conditions (e.g., “autist”). The medium slider setting for ableism will catch everything in the low setting plus generic references to some conditions (e.g., “retard”), as well as body shaming references (e.g., “fatso”). The highest setting will catch all ableist references including general physical insults (e.g., “midget” used in a derogatory way).
This filter catches language about doing harm to others or expressing someone should harm themselves. The interpretation for this classifier is quite heavily influenced by context, so results will vary depending on the combination of words that precede a term. On the low slider setting this filter will catch the most aggressive language including violent threats (e.g., threats to “stab” someone or phrases like “get fucked”). The medium slider setting for aggression includes everything from the low setting plus more moderate violent threats (e.g., threats including “slap” and similar words). The highest setting will filter any language that appears to be a threat including words like “kill” or “die” even if used in a gaming context.
This filter catches negative language about somebody’s gender identity and or sexual orientation. It is worth noting that words like “gay”, or “lesbian” are considered neutral unless they coincide with context that suggests they are being used in a hateful way. At the low slider setting the filter will catch only the most negative language about LGBTQ+ groups (e.g., “fudgepacker”). On the medium setting anything from the low setting will be caught plus more moderate disparaging LGBTQ+ language (e.g., “lezzer”). On the high setting the filter will catch language from low and medium settings and any other potentially homophobic (e.g., “no homo”) or negative language about LGBTQ+ communities.
This filter catches language that is disparaging towards women. On the low setting the filter catches the most derogatory speech about women such as “whore”. The medium setting includes moderately negative speech about women (e.g., “bitch”), as well as anything caught by the low setting. On the high setting any speech that is disparaging to women will be caught (e.g., “pussy” used in a non-sexual way)
This filter catches language that is targeted at a specific person or a group of people in an attempt to disparage them. This classifier is very extensive and has quite a lot of overlap with terms related to identity hate, homophobia, racism, and xenophobia. On the low setting, language will be caught that covers the most offensive name-calling terms and those that overlap connote racist, misogynist, homophobic, etc. intent and variations of this type of language. On the medium setting, everything from the low category and more moderate name-calling (e.g., “asshole”) will be caught. On the high setting all name-calling references will be caught, even more minor ones (e.g., “noob”, “dumbass”, etc.)
This filter will catch all forms of the n-word including more minor variation such as those ending with “er” and “a” or “ah”. This filter is binary (on/off) as there is little variation between any form of the n-word that can be detected in audio.
This filter catches language that is aimed at disparaging someone or a group of people based on their ethnicity or origin. This filter is binary (on/off) as there is little gradation in the severity of various forms of racist and xenophobic language.
This filter catches language that is of a sexual nature. On the low setting this filter catches language that covers sexual references to body parts and many sexual terms and acts. At medium setting this filter will catch language caught by the low setting plus variations on moderate sexual language (e.g., “boobs”) On the high setting the filter will catch any sexual language caught by the low and medium settings plus minor sexual references and innuendo (e.g., “booty”, “horny”, etc.).
This filter will catch any form of profanity or adult language, and this overlaps with many of the other filters. On the low setting this filter will catch the n-word and other racist and xenophobic language combined with swearing, and other extreme forms of swearing. On the medium setting the filter will pick up language caught by the low setting plus variations on sexualized swearing (e.g., “cocksucker”) and most uses of “shit” and “fuck”, etc. At the highest setting all swearing will be caught including more minor swearing (e.g., “bastard”, “ass, “damn”, etc.)
This filter covers language used by white nationalist groups and general white supremacist language. This includes anti-Semitic speech and coded speech used by white nationalists attempting to find each other in a group. Much of the coded speech and verbal symbology that led to the development of this classifier can be found on the ADL website: https://www.adl.org/hate-symbols This filter is binary (on/off) as there is little gradation in this filter.
Annotated Transcript: The transcript view includes highlights for all the language detected by Bleep. For each paragraph, the list of detected categories is shown to the right of the transcript. Note that the highlights may not be a one-to-one reflection of what was redacted.
Conversation Temperature : The temperature chart acts as a running guide of the overall toxicity of the conversation. When there is prolonged toxicity, the temperature will rise to reach that level of toxicity. When there is prolonged conversation without toxicity or periods of silence, the temperature will reflect the fact there is a “cooling off”. The temperature chart is updated when there is new transcript data. If there is prolonged silence, the temperature chart will be updated upon the analysis of the next utterance.
© 2022 Intel Corporation | Intel, the Intel logo, Intel Core and Intel Inside are trademarks of Intel Corporation in the U.S. and/or other countries. | *Other names and brands may be claimed as property of others.
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OCAU Merchandise is available! Check out our 20th Anniversary Mugs , Classic Logo Shirts and much more ! Discussion in this thread .
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did you install the Microsoft UAA architecture driver before installing the Realtek driver?
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download and run RMAA if you can, might show up major issues.
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What's this RMAA you guys speak of ?
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I just ran the test with my SB Live!
Frequency response (from 40 Hz to 15 kHz), dB: +0.27, -0.32 Good
Noise level, dB (A): -84.4 Good
Dynamic range, dB (A): 83.9 Good
THD, %: 0.0033 Very good
IMD + Noise, %: 0.021 Good
Stereo crosstalk, dB: -86.3 Excellent
IMD at 10 kHz, %: 0.022 Good
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Listening through a pair of Sennheiser headphones and my god I feel like the music has lost depth and become all weak.
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its an onboard sound chip...are we expecting miracles today are we
otherwise. are you using the front jacks, or plugging in straight from the back of the PC ?
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settle down mitch.
onboards aren't all that bad in my experience - i mean, i have soundmax onboard audio, and audio is probably one of the most important things on my computer, seeing as i tab, listen to music, create music, and all of that. I've found no problems with it, and a i frankly see no point in spending alot of money on a soundcard with useless features.
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Discussion in ' PC Audio ' started by tuppaware , Nov 9, 2005 .
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