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• 4 Ways to Embed User Privacy & Data Security in Your Business

  15 juillet 2022, par Erin — Privacy

  Customer analytics undeniably plays a vital role for businesses. Product improvements, interface personalisation, content improvements, and creative advertising thrive on data. 

  Yet, there’s a fine line between being a customer-centred company and a privacy-violating one. 

  Due to ubiquitous online tracking, 62% of Americans now believe that it’s impossible to go about their daily lives without companies collecting data about them. Still, despite the importance of privacy in business for consumers, companies are reluctant to act. Privacy initiatives often stay on the back burner due to perceived complexity. That’s true to some extent.

  Privacy in business does assume complex technical changes to your data management. But to be a privacy-centred organisation, you also need to re-think your processes, practices, and culture. 

  Here are four ways to start your journey to better user privacy and data security. 

  1. Revise Your Data Collection Process to Gain Consumer Trust 

  The public is wary of sharing data with businesses because they are suspicious of its subsequent usage. 

  However, not all data collection is bad or wrong. In many cases, you need specific data for service delivery, compliance, or good-natured personalisation. 

  That’s exactly what consumers expect. Almost half of US consumers say they’d trust a company that limits the amount of personal information requested and only asks for data relevant to its products/services. 

  By limiting data collection and offering transparent data usage terms, you can : 

  • Reassure reluctant users to try your product or service — hence, boost conversions and sales. 
  • Retain existing audiences by gaining their trust, which leads to loyalty and higher customer lifetime value (CLV). 

  To gain consumers’ trust, implement proper consent and opt-out mechanisms. Then create educational materials about how you are collecting and using their data.

  2. Perform Data Mapping to Determine Where Sensitive Data Rests 

  Businesses are already pressed with an expanded cyber-security radar, courtesy of remote work, digital payment processing, IoT device adoption, etc. Yet, 41% of the executives don’t think their security initiatives have kept up with the digital transformations.

  Loopholes in security eventually result in a data breach. The average cost of a data breach looms at $4.24 million globally. The sum includes regulatory fines and containment costs, plus indirect losses in the form of reduced brand equity and market share. 

  Lax data protection in business also undermines consumer trust : 87% of consumers wouldn’t transact with a company if they had qualms with its security practices. 

  To improve your security posture, analyse where you are storing sensitive consumer data, who has access to it (internally and externally), and how you are protecting it. Then work with cybersecurity specialists on implementing stronger consumer security mechanisms (e.g. auto-log offs, secure password policy, etc) and extra internal security policies (if needed). 

  At the same time, start practising data minimisation. Ensure that all collected data is : 

  • Adequate – sufficient to meet your stated objectives 
  • Relevant – is rationally linked to the objectives 
  • Limited – no unnecessary data is collected or stored
  • Timely – data is periodically reviewed and removed when unnecessary 

  

  These principles prevent data hoarding. Also, they help improve your security posture and regulatory compliance by reducing the volume of information you need to safeguard.

  3. Do an Inventory of Your Business Tools

  Data leaks and consumer privacy breaches often occur through third parties. Because Google Analytics was deemed in breach of European GDPR in France, Austria and Italy, businesses using it are vulnerable to lawsuits (which are already happening). 

  Investigate your corporate toolkit to determine “weak links” – tools with controversial privacy policies, murky data collection practices, and poor security. 

  Treat it as a journey and pick your battles. By relying on Big Tech products for years, you might have overlooked better alternatives. 

  For example :

  • Matomo is a privacy-centred Google Analytics alternative. Our web analytics is compliant with GDPR, CCPA, and other global privacy laws. Unlike Google Analytics, we don’t exploit any data you collect and provide full transparency into how and where it’s stored. Or if you want a simple analytics solution, Fathom is another great privacy-friendly option.

  

  • For online data storage, you can choose Proton Drive or Nextcloud (open-source). Or host your corporate data with a local cloud hosting provider to avoid cross-border data transfers.

  

  Aim to progressively replace Google products with more privacy-centred alternatives. 

  4. Cultivate a Privacy-Centred Corporate Culture 

  To make privacy a competitive advantage, you need every team member (at every level) to respect its importance. 

  This is a continuous process of inspiring and educating your people. Find “privacy ambassadors” who are willing to lead the conversations, educate others, and provide resources for leading the change. 

  On an operational level, incorporate privacy principles around data minimisation, bounded collection, and usage into your Code of Conduct, standard operating procedures (SOPs), and other policies. 

  Creating a privacy-centric culture takes effort, but it pays off well. Cisco estimates that for each dollar spent on privacy, an average organisation gets $2.70 in associated benefits. Almost half (47%) of organisations gain 2X returns on their privacy initiatives.

  Moving Forward with a Data Privacy Programme 

  Privacy has become a strong differentiator for brands. Consumers crave transparency and ethical data usage. Regulators mandate limited data collection and proper security mechanisms.

  But sweeping changes are hard to implement. So start small and go one step at a time. Understand which first-party data your company collects and how it is stored.

  Then look into the tools and technologies you are using for data collection. Do these provide sufficient privacy controls ? How are they using data collected on your behalf ? Finally, move to wider transformations, pertaining to data management, cybersecurity, and cultural practices. 

  Be consistent with your effort — and eventually, all the pieces will fall into place. 

• Google Analytics Privacy Issues : Is It Really That Bad ?

  2 juin 2022, par Erin

  If you find yourself asking : “What’s the deal with Google Analytics privacy ?”, you probably have some second thoughts. 

  Your hunch is right. Google Analytics (GA) is a popular web analytics tool, but it’s far from being perfect when it comes to respecting users’ privacy. 

  This post helps you understand tremendous Google Analytics privacy concerns users, consumers and regulators expressed over the years.

  In this blog, we’ll cover :

  What Does Google Analytics Collect About Users ? 

  To understand Google Analytics privacy issues, you need to know how Google treats web users’ data. 

  By default, Google Analytics collects the following information : 

  • Session statistics — duration, page(s) viewed, etc. 
  • Referring website details — a link you came through or keyword used. 
  • Approximate geolocation — country, city. 
  • Browser and device information — mobile vs desktop, OS usage, etc. 

  Google obtains web analytics data about users via two means : an on-site Google Analytics tracking code and cookies.

  A cookie is a unique identifier (ID) assigned to each user visiting a web property. Each cookie stores two data items : unique user ID and website name. 

  With the help of cookies, web analytics solutions can recognise returning visitors and track their actions across the website(s).

  

  • First party cookies are generated by one website and collect user behaviour data from said website only. 
  • Third-party cookies are generated by a third-party website object (for example, an ad) and can track user behaviour data across multiple websites. 

  As it’s easy to imagine, third-party cookies are a goldmine for companies selling online ads. Essentially, they allow ad platforms to continue watching how the user navigates the web after clicking a certain link. 

  Yet, people have little clue as to which data they are sharing and how it is being used. Also, user consent to tracking across websites is only marginally guaranteed by existing Google Analytics controls. 

  Why Third-Party Cookie Data Collection By GA Is Problematic 

  Cookies can transmit personally identifiable information (PII) such as name, log in details, IP address, saved payment method and so on. Some of these details can end up with advertisers without consumers’ direct knowledge or consent.

  Regulatory frameworks such as General Data Protection Regulation (GDPR) in Europe and California Consumer Privacy Act (CCPA) emerged as a response to uncontrolled user behaviour tracking.

  Under regulatory pressure, Big Tech companies had to adapt their data collection process.

  Apple was the first to implement by-default third-party blocking in the Safari browser. Then added a tracking consent mechanism for iPhone users starting from iOS 15.2 and later. 

  Google, too, said it would drop third-party cookie usage after The European Commission and UK’s Competition and Markets Authority (CMA) launched antitrust investigations into its activity. 

  To shake off the data watchdogs, Google released a Privacy Sandbox — a set of progressive tech, operational and compliance changes for ensuring greater consumer privacy. 

  Google’s biggest promise : deprecate third-party cookies usage for all web and mobile products. 

  Originally, Google promised to drop third-party cookies by 2022, but that didn’t happen. Instead, Google delayed cookie tracking depreciation for Chrome until the second half of 2023. 

  Why did they push back on this despite hefty fines from regulators ?

  Because online ads make Google a lot of money.

  In 2021, Alphabet Inc (parent company of Google), made $256.7 billion in revenue, of which $209.49 billion came from selling advertising. 

  Lax Google Analytics privacy enforcement — and its wide usage by website owners — help Google make those billions from collecting and selling user data. 

  How Google Uses Collected Google Analytics Data for Advertising 

  Over 28 million websites (or roughly 85% of the Internet) have Google Analytics tracking codes installed. 

  Even if one day we get a Google Analytics version without cookies, it still won’t address all the privacy concerns regulators and consumers have. 

  Over the years, Google has accumulated an extensive collection of user data. The company’s engineers used it to build state-of-the-art deep learning models, now employed to build advanced user profiles. 

  Deep learning is the process of training a machine to recognise data patterns. Then this “knowledge” is used to produce highly-accurate predictive insights. The more data you have for model training — the better its future accuracy will be. 

  Google has amassed huge deposits of data from its collection of products — GA, YouTube, Gmail, Google Docs and Google Maps among others. Now they are using this data to build a third-party cookies-less alternative mechanism for modelling people’s preferences, habits, lifestyles, etc. 

  Their latest model is called Google Topics. 

  This comes only after Google’s failed attempt to replace cookie-based training with Federated Learning of Cohorts (FLoC) model. But the solution wasn’t offering enough user transparency and user controls among other issues.

  

  Google Topics promises to limit the granularity of data advertisers get about users. 

  But it’s still a web user surveillance method. With Google Topics, the company will continue collecting user data via Chrome (and likely other Google products) — and share it with advertisers. 

  Because as we said before : Google is in the business of profiting off consumers’ data. 

  Two Major Ways Google Takes Advantage of Customer Data

  Every bit of data Google collects across its ecosystem of products can be used in two ways :

  • For ad targeting and personalisation 
  • To improve Google’s products 

  The latter also helps the former. 

  Advanced Ad Personalisation and Targeting

  GA provides the company with ample data on users’ 

  • Recent and frequent searches 
  • Location history
  • Visited websites
  • Used apps 
  • Videos and ads viewed 
  • Personal data like age or gender 

  The company’s privacy policy explicitly states that :
  

  

  Google also admits to using collected data to “measure the effectiveness of advertising” and “personalise content and ads you see on Google.” 

  But there are no further elaborations on how exactly customers’ data is used — and what you can do to prevent it from being shared with third parties. 

  In some cases, Google also “forgets” to inform users about its in-product tracking.

  Journalists from CNBC and The New York Times independently concluded that Google monitors users’ Gmail activity. In particular, the company scans your inbox for recent purchases, trips, flights and bills notifications. 

  While Google says that this information isn’t sold to advertisers (directly), they still may use the “saved information about your orders in other Google services”. 

  Once again, this means you have little control or knowledge of subsequent data usage. 

  Improving Product Usability 

  Google has many “arms” to collect different data points — from user’s search history to frequently-travelled physical routes. 

  They also reserve the right to use these insights for improving existing products. 

  Here’s what it means : by combining different types of data points obtained from various products, Google can pierce a detailed picture of a person’s life. Even if such user profile data is anonymised, it is still alarmingly accurate. 

  Douglas Schmidt, a computer science researcher at Vanderbilt University, well summarised the matter : 

  “[Google’s] business model is to collect as much data about you as possible and cross-correlate it so they can try to link your online persona with your offline persona. This tracking is just absolutely essential to their business. ‘Surveillance capitalism’ is a perfect phrase for it.”

  Google Data Collection Obsession Is Backed Into Its Business Model 

  OK, but Google offers some privacy controls to users ? Yes. Google only sees and uses the information you voluntarily enter or permit them to access. 

  But as the Washington Post correspondent points out :

  “[Big Tech] companies get to set all the rules, as long as they run those rules by consumers in convoluted terms of service that even those capable of decoding the legalistic language rarely bother to read. Other mechanisms for notice and consent, such as opt-outs and opt-ins, create similar problems. Control for the consumer is mostly an illusion.”

  Google openly claims to be “one of many ad networks that personalise ads based on your activity online”. 

  The wrinkle is that they have more data than all other advertising networks (arguably combined). This helps Google sell high-precision targeting and contextually personalised ads for billions of dollars annually.

  Given that Google has stakes in so many products — it’s really hard to de-Google your business and minimise tracking and data collection from the company.
  

  They are also creating a monopoly on data collection and ownership. This fact makes regulators concerned. The 2021 antitrust lawsuit from the European Commission says : 

  “The formal investigation will notably examine whether Google is distorting competition by restricting access by third parties to user data for advertising purposes on websites and apps while reserving such data for its own use.”

  In other words : By using consumer data to its unfair advantage, Google allegedly shuts off competition.

  But that’s not the only matter worrying regulators and consumers alike. Over the years, Google also received numerous other lawsuits for breaching people’s privacy, over and over again. 

  Here’s a timeline : 

  • 2019 : UK citizens issued a class action suit against Google for imposing cookies to override users’ privacy settings in the Safari browser. 
  • 2020 : US citizens pushed for a $5 billion class-action suit for tracking their activity through browsers set in “private” mode.
  • 2022 : Another class-action lawsuit in the US for deceptive privacy controls and unconsented location data tracking by Google mobile apps. 
  • 2022 : Google reached a $100 million class-action settlement for breaching Illinois biometrics privacy laws in Google Photos. 

  Separately, Google has a very complex history with GDPR compliance. 

  How Google Analytics Contributes to the Web Privacy Problem 

  Google Analytics is the key puzzle piece that supports Google’s data-driven business model. 

  If Google was to release a privacy-focused Google Analytics alternative, it’d lose access to valuable web users’ data and a big portion of digital ad revenues. 

  Remember : Google collects more data than it shares with web analytics users and advertisers. But they keep a lot of it for personal usage — and keep looking for ways to share this intel with advertisers (in a way that keeps regulators off their tail).

  For Google Analytics to become truly ethical and privacy-focused, Google would need to change their entire revenue model — which is something they are unlikely to do.

  Where does this leave Google Analytics users ? 

  In a slippery territory. By proxy, companies using GA are complicit with Google’s shady data collection and usage practice. They become part of the problem.

  In fact, Google Analytics usage opens a business to two types of risks : 

  • Reputational. 77% of global consumers say that transparency around how data is collected and used is important to them when interacting with different brands. That’s why data breaches and data misuse by brands lead to major public outrages on social media and boycotts in some cases. 
  • Legal. EU regulators are on a continuous crusade against Google Analytics 4 (GA4) as it is in breach of GDPR. French and Austrian watchdogs ruled the “service” illegal. Since Google Analytics is not GDPR compliant, it opens any business using it to lawsuits (which is already happening).

  But there’s a way out.

  Choose a Privacy-Friendly Google Analytics Alternative 

  Google Analytics is a popular web analytics service, but not the only one available. You have alternatives such as Matomo. 

  Our guiding principle is : respecting privacy.

  Unlike Google Analytics, we leave data ownership 100% in users’ hands. Matomo lets you implement privacy-centred controls for user data collection.

  Plus, you can self-host Matomo On-Premise or choose Matomo Cloud with data securely stored in the EU and in compliance with GDPR.

  The best part ? You can try our ethical alternative to Google Analytics for free. No credit card required ! Start your free 21-day trial now. 

  21 day free trial. No credit card required.

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I hereby accept the terms and conditions and the data processing agreeement (DPA).

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  

  » Start improving your websites now

  

• FFMPEG — using 'amix' to combine short audio clip with a video results in final video's sound cutting off early

  12 avril 2022, par kilika

  I am trying to combine the following :

  


  (a) : 29s video clip that has its own audio that lasts the entire duration

  


  (b) : audio clip I want to play at the start of the video, in conjunction with original audio, and is 2 seconds long

  


  I successfully use 'amix' to obtain a video at the end with combined audio, but the problem is that the final video's audio cuts off at around 26 out of the 29 seconds of the video and goes silent.

  


  What doesn't make any sense is that the resulting video plays as it should, with the audio successfully mixed. But the output video's audio stream loses the last 3 seconds.

  


  Here's the 'amix' command I'm using (sending via subprocess) :

  


  subprocess.call(['ffmpeg','-i', input.mp4', '-i', "audioclip.mp3", '-filter_complex', 'amix', output.mp4'])


  


  I've also used versions of this command that spell out the -map "0:a" and -map "1:a", or tried using 'amix=inputs=2:duration:longest' among many other additions. All lead to the same problem : the final combined video's audio drops out with 3 seconds remaining in the video, even though the initial 'input.mp4' video has a full 29 out of 29 seconds of audio.

  


  Does anyone know why these last several seconds of audio from [a] are missing in the final video ?

  


  _________________________________________________________________

  


  edit : Below is my output when I run the amix command listed above :

  


  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'RuneBearinstakill_advanced.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf59.20.101
  Duration: 00:00:29.77, start: 0.000000, bitrate: 5441 kb/s
  Stream #0:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/bt470bg/smpte170m, progressive), 1920x1080 [SAR 1:1 DAR 16:9], 5304 kb/s, 30 fps, 30 tbr, 15360 tbn (default)
    Metadata:
      handler_name    : Bento4 Video Handler
      vendor_id       : [0][0][0][0]
  Stream #0:1[0x2](eng): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
    Metadata:
      handler_name    : Bento4 Sound Handler
      vendor_id       : [0][0][0][0]
[mp3 @ 000001f0c8ec2040] Estimating duration from bitrate, this may be inaccurate
Input #1, mp3, from 'TTS_clip.mp3':
  Duration: 00:00:01.90, start: 0.000000, bitrate: 32 kb/s
  Stream #1:0: Audio: mp3, 24000 Hz, mono, fltp, 32 kb/s
Stream mapping:
  Stream #0:1 (aac) -> amix (graph 0)
  Stream #1:0 (mp3float) -> amix (graph 0)
  amix:default (graph 0) -> Stream #0:0 (aac)
  Stream #0:0 -> #0:1 (h264 (native) -> h264 (libx264))
Press [q] to stop, [?] for help
[libx264 @ 000001f0c8cbe5c0] using SAR=1/1
[libx264 @ 000001f0c8cbe5c0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
[libx264 @ 000001f0c8cbe5c0] profile High, level 4.0, 4:2:0, 8-bit
[libx264 @ 000001f0c8cbe5c0] 264 - core 164 r3094 bfc87b7 - H.264/MPEG-4 AVC codec - Copyleft 2003-2022 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=24 lookahead_threads=4 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'RuneBearinstakill_advancedwithtts.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf59.20.101
  Stream #0:0: Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s
    Metadata:
      encoder         : Lavc59.25.100 aac
  Stream #0:1(eng): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt470bg/bt470bg/smpte170m, progressive), 1920x1080 [SAR 1:1 DAR 16:9], q=2-31, 30 fps, 15360 tbn (default)
    Metadata:
      handler_name    : Bento4 Video Handler
      vendor_id       : [0][0][0][0]
      encoder         : Lavc59.25.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
frame=  893 fps=110 q=-1.0 Lsize=   18717kB time=00:00:29.66 bitrate=5168.5kbits/s speed=3.66x    
video:18256kB audio:433kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.150179%
[aac @ 000001f0c8f9ebc0] Qavg: 921.259
[libx264 @ 000001f0c8cbe5c0] frame I:4     Avg QP:21.33  size: 71366
[libx264 @ 000001f0c8cbe5c0] frame P:633   Avg QP:23.32  size: 23837
[libx264 @ 000001f0c8cbe5c0] frame B:256   Avg QP:25.22  size: 12968
[libx264 @ 000001f0c8cbe5c0] consecutive B-frames: 57.2% 10.3% 10.1% 22.4%
[libx264 @ 000001f0c8cbe5c0] mb I  I16..4: 17.9% 71.4% 10.8%
[libx264 @ 000001f0c8cbe5c0] mb P  I16..4:  6.9% 17.6%  0.8%  P16..4: 43.1%  6.5%  1.5%  0.0%  0.0%    skip:23.6%
[libx264 @ 000001f0c8cbe5c0] mb B  I16..4:  1.5%  4.2%  0.3%  B16..8: 39.7%  4.6%  0.5%  direct: 1.6%  skip:47.6%  L0:55.9% L1:41.8% BI: 2.3%
[libx264 @ 000001f0c8cbe5c0] 8x8 transform intra:69.5% inter:87.3%
[libx264 @ 000001f0c8cbe5c0] coded y,uvDC,uvAC intra: 35.6% 26.8% 0.8% inter: 13.4% 10.8% 0.0%
[libx264 @ 000001f0c8cbe5c0] i16 v,h,dc,p: 21% 37% 12% 30%
[libx264 @ 000001f0c8cbe5c0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 25% 26% 21%  4%  5%  5%  6%  4%  5%
[libx264 @ 000001f0c8cbe5c0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 24% 28% 15%  5%  7%  7%  7%  5%  4%
[libx264 @ 000001f0c8cbe5c0] i8c dc,h,v,p: 67% 18% 14%  1%
[libx264 @ 000001f0c8cbe5c0] Weighted P-Frames: Y:0.2% UV:0.0%
[libx264 @ 000001f0c8cbe5c0] ref P L0: 72.3% 15.4%  8.7%  3.6%  0.0%
[libx264 @ 000001f0c8cbe5c0] ref B L0: 88.9%  9.5%  1.6%
[libx264 @ 000001f0c8cbe5c0] ref B L1: 97.7%  2.3%
[libx264 @ 000001f0c8cbe5c0] kb/s:5024.13


  


  And here is the output when I check the stream durations for the input video and the output video, showing how the output video's audio stream is somehow reduced by several seconds after the amix :

  


  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'RuneBearinstakill_advanced.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf59.20.101
  Duration: 00:00:29.77, start: 0.000000, bitrate: 5403 kb/s
  Stream #0:0[0x1](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/bt470bg/smpte170m, progressive), 1920x1080 [SAR 1:1 DAR 16:9], 5266 kb/s, 30 fps, 30 tbr, 15360 tbn (default)
    Metadata:
      handler_name    : Bento4 Video Handler
      vendor_id       : [0][0][0][0]
  Stream #0:1[0x2](eng): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
    Metadata:
      handler_name    : Bento4 Sound Handler
      vendor_id       : [0][0][0][0]
[STREAM]
duration=29.766667
[/STREAM]
[STREAM]
duration=29.738000
[/STREAM]

Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'RuneBearinstakill_advancedwithtts.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf59.20.101
  Duration: 00:00:29.77, start: 0.000000, bitrate: 5098 kb/s
  Stream #0:0[0x1](und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
    Metadata:
      handler_name    : SoundHandler
      vendor_id       : [0][0][0][0]
  Stream #0:1[0x2](eng): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt470bg/bt470bg/smpte170m, progressive), 1920x1080 [SAR 1:1 DAR 16:9], 4971 kb/s, 30 fps, 30 tbr, 15360 tbn (default)
    Metadata:
      handler_name    : Bento4 Video Handler
      vendor_id       : [0][0][0][0]
[STREAM]
duration=27.477000
[/STREAM]
[STREAM]
duration=29.766667