Muvox LLC v. Bmg Rights Management GmbH

I. Executive Summary and Procedural Information

• Parties & Counsel:
  • Plaintiff: Muvox LLC (New Mexico)
  • Defendant: Bmg Rights Management GmbH (Germany)
  • Plaintiff’s Counsel: Rabicoff Law LLC
• Case Identification: 2:24-cv-00655, E.D. Tex., 08/11/2024
• Venue Allegations: Venue is alleged to be proper on the basis that the defendant is a foreign corporation.
• Core Dispute: Plaintiff alleges that Defendant’s music streaming products or services infringe a patent related to the automated analysis, categorization, and playlist creation of music tracks based on computer-derived acoustic attributes.
• Technical Context: The technology at issue addresses methods for automatically analyzing audio data to classify music by characteristics like "mood," a central feature in modern digital music services for generating personalized user experiences.
• Key Procedural History: The asserted patent claims priority back to a 2014 provisional application and is the result of a lengthy and complex prosecution history involving a chain of numerous continuation and continuation-in-part applications.

Case Timeline

II. Technology and Patent(s)-in-Suit Analysis

U.S. Patent No. 11,899,713 - "Music streaming, playlist creation and streaming architecture"

• Issued: February 13, 2024.

The Invention Explained

• Problem Addressed: The patent's background section describes a challenge faced by music publishers who own catalogs of music but lack a practical way to provide a modern, personalized streaming experience to end users, distinct from the large, closed platforms like Spotify or Apple Music (ʼ713 Patent, col. 1:47-67).
• The Patented Solution: The invention proposes a system where music is analyzed to derive objective "rhythm, texture and pitch (RTP) scores," which are then used to categorize tracks and create playlists based on corresponding "moods." These scores are stored in a universal database. A publisher can then sponsor a branded end-user application that allows users to create personalized playlists exclusively from that publisher's catalog, using the sophisticated mood-based filtering, thereby giving publishers a direct channel to consumers (ʼ713 Patent, col. 2:5-34).
• Technical Importance: The described architecture aimed to provide individual rights holders with the same type of data-driven, personalized playlisting technology employed by major streaming services, while allowing them to maintain control over their content and brand identity (ʼ713 Patent, col. 2:27-34).

Key Claims at a Glance

• The complaint refers to "Exemplary '713 Patent Claims" without identifying them, but independent claim 1 is representative of the asserted method.
• Independent Claim 1 requires, in essence:
  • Selecting a song based on a "computer-derived comparison" between a "representation of the song" and known similarities in representations of other songs.
  • The comparison relies on a "human-trained machine".
  • The song's "representation" is based on isolating and identifying its "frequency characteristics".
  • The representations of the "other songs" are based on a "human listening" to them to identify their frequency characteristics.
  • These "frequency characteristics" correspond to one or more "moods".
  • The final selection is based on the similarity between the "moods" of the song and the "moods" of the other songs.
• The complaint incorporates by reference charts that identify the asserted claims, but these charts were not publicly filed with the complaint (Compl. ¶13).

III. The Accused Instrumentality

Product Identification

The complaint accuses "Exemplary Defendant Products" but does not identify them by name (Compl. ¶11). It states that the products are identified in charts included as Exhibit 2, which was not filed with the complaint (Compl. ¶13-14).

Functionality and Market Context

The complaint does not provide sufficient detail for analysis of the accused products' specific functionality or market context, instead incorporating by reference the non-provided Exhibit 2 (Compl. ¶13).

IV. Analysis of Infringement Allegations

The complaint’s substantive infringement allegations are contained in claim chart exhibits that were not provided with the initial filing (Compl. ¶13-14). The complaint’s narrative theory alleges that Defendant’s unidentified products perform the patented methods of music analysis and playlist creation, thereby satisfying all elements of the asserted claims either literally or under the doctrine of equivalents (Compl. ¶11, ¶13).

No probative visual evidence provided in complaint.

Identified Points of Contention

• Scope Questions: A central issue may be whether the accused products' song selection and recommendation engine constitutes a "computer-derived comparison" based on "frequency characteristics" as required by the patent. The dispute may turn on whether the accused system relies on such audio analysis or on alternative data, such as editorially assigned genre tags, user-generated playlists, or collaborative filtering data, which may fall outside the claim scope.
• Technical Questions: What evidence does the complaint provide that the accused system is a "human-trained machine"? The infringement analysis will likely depend on whether Defendant's system uses a machine learning model (e.g., a neural network) that was trained using a corpus of music tracks previously categorized by human listeners, as the patent specification describes (ʼ713 Patent, col. 17:33-40).

V. Key Claim Terms for Construction

The Term: "human-trained machine"

• Context and Importance: This term appears to be the inventive core of the claimed method, distinguishing it from simple algorithmic sorting. The viability of the infringement claim will depend heavily on whether Defendant’s system can be characterized as such a "machine."
• Intrinsic Evidence for a Broader Interpretation: The claim language itself is general. Plaintiff may argue it is broad enough to cover any system where human feedback or labeling is used to refine or train a classification algorithm, not just the specific neural network examples in the specification (ʼ713 Patent, col. 17:33-40).
• Intrinsic Evidence for a Narrower Interpretation: Defendant may argue the term should be limited by the specification’s detailed examples, which describe training a neural network on a pre-existing, human-labeled set of tracks to derive RTP scores. This could narrow the term to a specific type of supervised machine learning implementation (ʼ713 Patent, col. 4:35-54; col. 18:35-43).

The Term: "representation of the song"

• Context and Importance: The definition of this term dictates what technical data is being compared. Infringement will depend on whether the data structure used by the accused product qualifies as a "representation" under the patent.
• Intrinsic Evidence for a Broader Interpretation: The term itself is broad. Dependent claim 2 specifies the representation is an "audio fingerprint," which suggests the independent claim is not limited to that specific form and could cover other data structures that represent a song's attributes.
• Intrinsic Evidence for a Narrower Interpretation: The specification consistently describes the representation as being derived directly from the audio signal, such as a "spectrogram," "chromagram," or "mel-spectrogram" (ʼ713 Patent, col. 3:38-54). An argument could be made that the term is limited to such direct audio-derived data, as opposed to high-level metadata like genre or artist tags.

VI. Other Allegations

• Indirect Infringement: The complaint does not allege specific facts to support claims for induced or contributory infringement.
• Willful Infringement: While the body of the complaint does not contain an explicit allegation of willful infringement, the prayer for relief requests a finding that the case is "exceptional within the meaning of 35 U.S.C. § 285" (Compl. ¶E.i). This request preserves the plaintiff's ability to seek enhanced damages or attorneys' fees should facts supporting willfulness or other litigation misconduct emerge during the case.

VII. Analyst’s Conclusion: Key Questions for the Case

• A core issue will be one of technical implementation: Does the defendant's system for music categorization and playlisting rely on a "human-trained machine" that analyzes intrinsic "frequency characteristics" of the audio itself, as claimed in the patent, or does it operate on different principles such as collaborative filtering, analysis of textual metadata, or purely editorial curation?
• A key secondary issue will be one of definitional scope: Can the patent’s term "moods," which the specification ties to specific emotional states (e.g., "sad," "peaceful") derived from objective RTP scores, be construed broadly enough to read on the more functional or activity-based categories (e.g., "focus," "workout," "party") commonly employed by modern music streaming services?